4-b wellington cbd paramics model validation …...4-b wellington cbd paramics model validation...

Technical Report 4: Assessment of Traffic and Transportation Effects

Opus International Consultants Ltd

4-B Wellington CBD Paramics Model Validation

Report

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Heading 1 Heading 2

�Wellington�CBD�Paramics�Modelling�

Validation�Report�

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CER�09/112�

� Wellington�CBD�Paramics�Modelling�� Validation�Report��

� November�2009�

Opus International Consultants Limited Wellington Office Level 7, The Majestic Centre 100 Willis Street, PO Box 12003 Wellington 6144, New Zealand Telephone: +64 9 355 9500 Facsimile: +64 9 355 9585 Date: 02/11/09 Reference: 5-C1574.00 Status: Final

Wellington�CBD�Paramics�Modelling�Validation�Report�

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Document�Status�

Revision�Number�

Date�Section/�

Page�Author� Description�

0 05/09 ALL R Sprosen Draft for Discussion

1 06/09 ALL R Sprosen Draft for Discussion

2 11/09 ALL R Sprosen Final Document

Quality�Assurance�Statement�

Wellington�CBD�Paramics�Modelling�–�Validation�Report�

Prepared by Richard Sprosen, Transportation

Specialist

Prepared for the New�Zealand�Transport�Agency�

Reviewed by Fraser Fleming, Principal Transportation Modeller/

Nathan Harper, Transportation Modelling Team Leader

Draft Report Approved by David Dunlop, Transportation

Team leader

File Path: g:\transport\transit\proj\5-c1574.00 wellington paramics model extension\report\wicb validation report 2009 - v3.1.doc

Copyright�and�Disclaimers�

This document is the property of Opus International Consultants Limited. Any unauthorised employment or reproduction, in full or part is forbidden. This document has been prepared for the use of the New�Zealand�Transport�Agency�only.

©�Opus�International�Consultants�Limited�2009�


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Table�of�Contents�

Executive�Summary......................................................................................................................1

1 Introduction ..........................................................................................................................2

1.1 Appointment .....................................................................................................................2

1.2 Intended Use .....................................................................................................................2

1.3 Study Area .........................................................................................................................4

1.4 Report Structure................................................................................................................5

2 Data�Collection......................................................................................................................6

2.1 Traffic Count Data .............................................................................................................6

2.2 Traffic Queue Data ............................................................................................................8

2.3 Journey Time Data ............................................................................................................9

2.4 Signalised Intersection – Operational Data ....................................................................10

3 Demand�Matrix�Development .............................................................................................11

3.1 Matrix Estimation............................................................................................................11

3.2 Trip Length Distributions.................................................................................................13

3.3 Matrix Splitting................................................................................................................15

3.4 Demand Totals ................................................................................................................15

3.5 Release Profiles ...............................................................................................................16

4 Model�Development ...........................................................................................................19

4.1 Model Periods .................................................................................................................19

4.2 Public Transport ..............................................................................................................20

4.3 Network Coding ..............................................................................................................21

4.4 Global Parameters...........................................................................................................26

5 Model�Calibration ...............................................................................................................31

5.1 Statistical Convergence...................................................................................................31

5.2 Turning Volumes .............................................................................................................35

5.3 Link Counts ......................................................................................................................40

5.4 Screenlines ......................................................................................................................41

5.5 Journey Times .................................................................................................................44

5.6 Queue Lengths ................................................................................................................45

5.7 Visual Validation..............................................................................................................46

5.8 Peak Shoulder Periods ....................................................................................................49

5.9 Signal Timing ...................................................................................................................50


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6 Peer�Review ........................................................................................................................52

7 Forecasting..........................................................................................................................53

7.1 Methodology...................................................................................................................53

7.2 2016 and 2026 Traffic Demand.......................................................................................56

7.3 2016 and 2026 Network Operation ................................................................................57

Appendices

Appendix A Turn Validation Data Appendix B Journey Time Distance/Time Graphs Appendix C Data Collection Maps Appendix D Signal Timing Appendix E Peer Review Report


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Executive�Summary�

The New Zealand Transport Agency (NZTA) has commissioned Opus International Consultants (OPUS) to develop an S-Paramics micro-simulation model of the southern Wellington CBD. The model study area covers (approximately) the southern half of the Wellington CBD as well as an area out to the west beyond the Terrace Tunnel. This model has been developed for the representative AM peak, Inter peak and PM peak periods.

In order to ensure the model was accurately portraying the operation of the CBD a significant data collection exercise has been undertaken. The collection of data included turn counts, tube counts, queue lengths, journey times, and signal timing data and was carried out in February and March 2009. This data has been used to develop well calibrated models.

The S-Paramics models have been developed utilising an adaptive signal approach to the modelling of traffic signals through the incorporation of SCATS. This has been possible due to the development of Fuse, a software package that links the on-street traffic signal management software (SCATS) to S-Paramics. By utilising this system, modelled vehicles are controlled at intersections via the SCATS signal personalities which simulate the signal phasing as is experienced in reality.

Model development was carried out between March and June 2009. The development process involves three stages; network coding, traffic demand estimation and calibration/validation.

Network coding was done using a combination of aerial photography, as-built drawings of the inner-city bypass and on-site observations. The network coding involved an update of the existing Wellington CBD S-Paramics model developed in 2004 and the extension of the model to the east and south.

Traffic demand was forecasted by using the validated 2006 Wellington City SATURN model in conjunction with traffic counts carried out in 2009. The SATURN model has been developed from the larger Wellington area WTSM strategic model. This has enabled consistency with traffic patterns in the CBD area whilst adjusting the overall demand to be representative of 2009 traffic flows.

The calibration/validation process aims to ensure that the models developed are representative of observed conditions and meet measureable criteria to determine this. In the absence of any preferred New Zealand standards two sets of guidelines have been used in the calibration/validation process for the Wellington CBD S-Paramics models. These two guidelines are the DMRB (United Kingdom) guidelines and the EEM guidelines.

This report discusses the data collection, model development and calibration/validation process undertaken and the model performance against the applied guidelines. From the results shown in this report, it is our professional opinion and that of our peer reviewer, that the Wellington CBD S-Paramics models developed are representative of the operation of the Wellington CBD area and as such are fit for use in any future testing of the proposed schemes.


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1 Introduction�

1.1 Appointment�

Opus International Consultants Ltd. have been commissioned by the New Zealand Transport Agency (NZTA) to develop S-Paramics micro-simulation models of the Wellington CBD area. The key components to this commission are;

� Data Collection

� Model Development

� Calibration/Validation

� Forecasting

1.2 Intended�Use�

The models have been developed so that future land use changes and network improvements within the Wellington CBD can be assessed in terms of network operation and delay.

The Wellington CBD S-Paramics models form 1 of 3 packages utilised in the assessment of traffic in the Wellington area. The Wellington Transport Strategy Model (WTSM) EMME/2 models assess land use, SATURN models assessing traffic assignment and the S-Paramics models assessing network operation. The diagram shown in Figure 1-1 illustrates the relationships between these three approaches to transport modelling.

A key purpose of the models developed will be the investigation of proposed network improvements in the Basin Reserve area. Specifically it is proposed that westbound traffic travelling from the Mt Victoria Tunnel be given an alternative route around the northern side of the Basin Reserve either via a at-grade option or a grade separated over-bridge. This will alleviate traffic around the congested Basin Reserve ‘roundabout’ and enable the addition of bus lanes and additional public transport priority.


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Figure�1�1:�Model�Inter�relationships�

Figure 1-1 shows that as we decrease the size of the model area, the level of detail being modelled increases. Therefore, applying this to the Wellington traffic models, the WTSM (EMME/2) regional model identifies the traffic effects of future land use changes and population increases in the Wellington region. These predictions are used in the Wellington City SATURN model to identify routing and congestion issues on strategic routes throughout the Wellington City Council area. Finally this routing information is taken into account in S-Paramics and the detailed network operation is examined, in this case in the southern CBD area.

EMME/2

Wellington Region

SATURN

Wellington City

PARAMICS

Wellington CBD

Increased Level of Detail

Larger Model Area


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1.3 Study�Area�

Figure 1-2 below shows the extents of the model study area. This area was chosen to be representative of the likely effects of network changes around the Basin Reserve.

Figure�1�2�:�Wellington�CBD�S�Paramics�Model�–�Study�Area�

A more detailed map showing the exact cordon area of the S-Paramics model can be found in Appendix C.


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1.4 Report�Structure�

The purpose of this report is to provide the details of the development, calibration/validation and future year forecasting of the Wellington CBD S-Paramics models.

Sections contained in this report are as follows:

� Data Collection;

� Demand Matrix Development;

� Model Development;

� Calibration and Validation Results; and

� Forecasting


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2 Data�Collection�

A key objective of this study is to build a micro-simulation traffic model that is capable of reflecting traffic behaviour and conditions that occur in the real world. It is only when this has been achieved that the model can be used with any degree of confidence to examine the effects of future network changes.

In order to achieve this it is necessary to collect information on current traffic volumes and network conditions. This includes;

� Manual Classified Turning Counts;

� Link Counts;

� Queue Lengths;

� Journey Times; and

� Signalised Intersection Information

This data, used for the development and calibration/validation of the Wellington CBD S-Paramics models, was collected during February and March 2009.

2.1 Traffic�Count�Data�

A large number of manual classified intersection turning count surveys were carried out in February and March of 2009 for use in the demand matrix development. Each intersection was surveyed between 07:00 – 09:00, 11:00 – 13:00 and 16:00 – 18:00 on either a Tueday, Wednesday or Thursday.

The intersections counted were;

� Wellington Road / Evans Bay Parade

� Wellington Road / Kilbirnie Crescent

� Wellington Road / Moxham Avenue

� Wellington Road / Ruahine Street

� Moxham Avenue / Goa Street

� Moxham Avenue / Taurima Street

� Ruahine Street / Taurima Street


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� Paterson Street / Dufferin Street

� Adelaide Road / Rugby Street

� Rugby Street (western corner of the Basin Reserve)

� Sussex Street / Buckle Street

� Buckle Street / Cambridge Terrace

� Buckle Street / Kent Terrace

� Dufferin Street / Hania Street

� Dufferin Street / Ellice Street

� Vivian Street / Cambridge Terrace / Kent Terrace

� Courtney Place / Cambridge Terrace / Kent Terrace

� Tasman Street / Buckle Street

� Vivian Street / Tory Street

� Courtney Place / Tory Street

� Buckle Street / Taranaki Street

� Vivian Street / Taranaki Street

� Ghuznee Street / Taranaki Street

� Courtney Place / Taranaki Street

� Karo Drive / Cuba Street

� Karo Drive / Victoria Street

� Vivian Street / Victoria Street

� Ghuznee Street / Victoria Street

� Dixon Street / Victoria Street

� Manners Street / Victoria Street

� Karo Drive / Willis Street


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� Vivian Street / Willis Street

� Ghuznee Street / Willis Street

� Dixon Street / Willis Street

� Manners Street / Willis Street

These counts were collected over a two week period and therefore have been balanced to be a consistent representation of the base date 04/03/09.

In addition to these counts, tube counts were carried out at the following locations:

� Aro Street

� Brooklyn Road

� Victoria Street (northern extent of the model)

� Willis Street (northern extent of the model)

The link count volumes from the tube data was used to assess peak period and peak hour information as well as assessing the amount of daily variation the occurs in traffic levels.

In addition to providing link count volumes at the model extents, tube counts were used to gather speed and headway data used in the calibration of the model.

A map of the data collection locations can be found in Appendix C.

2.2 Traffic�Queue�Data�

Vehicle queue length surveys were undertaken at a number of signalised intersections whilst turning count surveys were being carried out. This maximum queue length survey involved observations of lane by lane queues at the start of the green phase on each approach. The intersections surveyed for queue lengths were:

� Tasman Street / Buckle Street

� Vivian Street / Tory Street

� Courtney Place / Tory Street

� Buckle Street / Taranaki Street

� Vivian Street / Taranaki Street

� Ghuznee Street / Taranaki Street


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� Courtney Place / Taranaki Street

� Karo Drive / Cuba Street

� Karo Drive / Victoria Street

� Vivian Street / Victoria Street

� Ghuznee Street / Victoria Street

� Dixon Street / Victoria Street

� Manners Street / Victoria Street

� Karo Drive / Willis Street

� Vivian Street / Willis Street

� Ghuznee Street / Willis Street

� Dixon Street / Willis Street

� Manners Street / Willis Street

2.3 Journey�Time�Data�

Six journey time routes have been identified to assess the models representation of travel time and delay. These routes are;

1. Westbound - SH1 from Evans Bay Parade to Willis Street

1. Eastbound - SH1 from Willis Street to Evans Bay Parade

2. Willis Street from Webb Street to Dixon Street

3. Victoria Street from Dixon Street to Webb Street

4. Northbound - Taranaki Street from Arthur Street to Wakefield Street

4. Southbound - Taranaki Street from Courtney Place to Arthur Street

Observed journey time data was recorded over a minimum of 10 runs on each route.

Observed journey times for each segment were both averaged and 95% confidence intervals using the t-statistic were calculated. Cumulative graphs were created and plotted with modelled average journey times to ensure these are within the bounds of the confidence interval and close to the observed average.


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A map of the journey time routes can be found in Appendix C.

2.4 Signalised�Intersection�–�Operational�Data�

The following data relating to signalised intersections has been collected during the surveyed period:

� SCATS Signal Personalities (downloaded from each signal controller by CLS Traffic Ltd.)

� SCATS Signal Timings as run during the survey period

� SCATS Loop Count Detections during the survey period

Signal timing and SCATS loop count data has been used during the development and calibration of the models to ensure correct lane utilisation and routing behaviour.

Signal operation data has been collected via BasePlus Fuse, with the interpretation of observed data and integration into S-Paramics carried out by Bill Sissons at BasePlus in Christchurch.

A map of the signalised intersection locations in the study area can be found in Appendix C.

A comparison of observed and modelled signal timings and phase splits can be found in Appendix D.


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3 Demand�Matrix�Development�

Modelled traffic demand is developed in the form of an origin – destination matrix. This matrix identifies the traffic demand between each entry and exit point on the network. These points can relate to roads entering/exiting the model area and internal areas where vehicles leave the network such as parking buildings or offices. The following section describes the development of traffic demand matrices for the Wellington CBD S-Paramics models.

3.1 Matrix�Estimation�

A Wellington City SATURN model has recently been developed and validated with a base year of 2006 (prior to the construction of the Inner City Bypass). The extents of the Wellington City SATURN model are shown in Figure 3-1. This model was subsequently updated to include the Inner City Bypass including the road layout changes that were constructed as part of this project. This model has been cordoned to match the S-Paramics model area (Figure 3-2). The cordon matrix from SATURN has been used as a prior matrix for the Paramics model.

Figure�3�1:�Wellington�City�SATURN�Model�


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Figure�3�2:�Wellington�CBD�SATURN�Model�Cordon�

Using the prior matrix from SATURN, the new manual classified turning counts and tube counts, constrained matrix estimation was carried out with restrictions placed on the alteration of minor zones.

Matrix estimation is the process of factoring up or down trips between an origin and a destination with the aim to adjust all trips to the minimum possible extent where by obsereved turning counts at each surveyed intersection are as closely represented as possible. During this process it is vital that the distribution of trip lengths is maintained so that very short trips are not increased to match a turning count at a particular intersection.

This process was carried out separately for light and heavy vehicles.

Minor alterations to the final matrices have been carried out during the calibration process.


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3.2 Trip�Length�Distributions�

By examining the length of trips in the prior matrix, compared to the length of trips in the estimated matrix, the matrix estimation process can be checked for errors in trip length distribution. The following graphs show a comparison of the prior matrices for each peak (AM, IP and PM) to the final estimated and calibrated matrices. This comparison has been done by grouping trips via their length, into 250m segments.

Figure�3�3:�Trip�Length�Distribution�–�AM�Peak�


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Figure�3�4:�Trip�Length�Distribution�–�IP�Peak�

Figure�3�5:�Trip�Length�Distribution�–�PM�Peak�


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The results shown in Figure 3-3, Figure 3-4 and Figure 3-5 indicate that the matrix estimation process is predominantly retaining the distribution of trip lengths to be consistent with the prior matrices from SATURN.

3.3 Matrix�Splitting�

During model calibration, a deficiency in the operation of Paramics was identified on Victoria Street and at the southern end of the Basin Reserve. Vehicles had the tendency to make unrealistic lane choice decisions due to a limited ability to ‘see’ decision points ahead.

For this reason, the matrices were separated into three unique matrices. One matrix for vehicles travelling northbound on the Inner City Bypass, one matrix for all traffic heading to Adelaide Road and one matrix for all other vehicles. This has enabled vehicle restrictions to force lane choice decisions at an earlier point.

3.4 Demand�Totals�

The following table shows the total vehicle demand for each period in each model.

Table�3�1:�Total�Traffic�Demand�

AM�Peak�Period� Inter�Peak�Period� PM�Peak�Period�

Pre�Load� 15,373 13,854 18,730

Peak� 16,927 14,659 19,561

Post�Load� 11,975 14,659 15,834

The pre-load hour and post-load hour for each peak was taken as a proportion of the peak hour matrix as per the following table:

Table�3�2:�Peak�Period�Demand�Proportions�

AM�Peak�Period� Inter�Peak�Period� PM�Peak�Period�

Pre�Load� 90% 95% 95%

Peak� 100% 100% 100%

Post�Load� 70% 100% 80%


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These percentages were developed from an average of hourly variation taken from tube count information.

3.5 Release�Profiles�

Release profiles define the proportion of traffic demand to be released from a zone in 5 minute segments. This enables the congestion build up on the network to be represented as occurs in reality.

Profiles were developed using a variety of data sources based on available information. A separate profile was developed for each external entry point into the model. In addition to this, 5 internal zone profiles were developed to represent each internal ‘sector’ within the model.

For each ‘external’ profile, the closest source of relevant data was used; SCATS counts, manual intersection counts or tube counts.

For each ‘internal’ profile, the average traffic throughput of intersection approaches within and surrounding each sector was used. For intersections surrounding the sector, only the approaches used by vehicles ‘departing’ were used to represent traffic coming ‘from’ the area.

Once the 5 minute release profiles were developed, the associated estimated demand matrices were ‘row-totalled’ and proportioned into 5 minute segments using each associated release profile on the appropriate zone totals. Using the graphed results of this analysis it was then possible to ‘smooth’ the transition between each 5 minutes and especially the transition between each modelled hour.

Table 3-3 below lists each profile and the associated geographic location.

Table�3�3:�Release�Profile�Descriptions�

Profile� Name� Location�

Profile 1 Brooklyn Road

All traffic from Brooklyn Road in the south western extent of the model

Profile 2 Nairn Street

All traffic from Nairn Street and the surrounding Mt Cook area

Profile 3 Wallace Street

All traffic from Wallace Street / Taranaki Street (south)

Profile 4 Adelaide Street All traffic from Adelaide Road

Profile 5 Wellington Road

All traffic from Wellington Road / Constable Street


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Profile 6 Kilbirnie Crescent

All traffic from Kilbirnie Street in the Kibirnie area in the south eastern area of the model

Profile 7 Evans Bay Parade

All traffic from the southern end of Evans Bay Parade in the Kilbirnie area

Profile 8 Cobham Drive

All traffic from Cobham Drive coming from the Airport area.

Profile 9 Evans Bay Parade

All traffic from Evans Bay Parade north of Wellington Road

Profile 10 Hamilton Road All traffic from Hamilton Road in the Hataitai area

Profile 11 Hataitai Road All traffic from Hataitai north of Taurima Street

Profile 12 Elizabeth Street All traffic from the Mt Victoria area

Profile 13 Majoribanks Street

Traffic from Majoribanks Street (alternative to the tunnel)

Profile 14 Cambridge Terrace All traffic from Oriental Parade area

Profile 15 Tory Street All traffic from the northern end of Tory Street

Profile 16 Taranaki Street

All traffic from the northern end of Taranaki Street

Profile 17 Cuba Street All traffic from Cuba Street

Profile 18 Victoria Street

All traffic from the northern end of Victoria and surrounding area

Profile 19 Willis Street All traffic from the northern end of Willis Street

Profile 20 Boulcott Street All traffic from Boulcott Street

Profile 21 Wellington Urban

Motorway All traffic from the northern extent of the

motorway

Profile 22 Ghuznee Street All traffic from the western end of Ghuznee Street

Profile 23 Vivian Street

All traffic from the western end of Vivian Street, Abel Smith Street and Aro Street


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Profile 24 Internal 1

Traffic originating in zones contained in the north western internal block bound by Vivian Street, Taranaki Street, Dixon Street and Willis Street

Profile 25

Internal 2

Traffic originating in zones contained in the north eastern internal block bound by Vivian Street,

Cambridge Terrace, Courtney Place and Taranaki Street


Traffic originating in zones contained in the south western internal block bound by Arthur Street, Taranaki Street, Vivian Street and Willis Street

Profile 27

Internal 4

Traffic originating in zones contained in the south western internal block bound by Buckle Street, Cambridge Terrace, Vivian Street and Taranaki

Street


All traffic originating from internal zones south of the inner city bypass and west of Tasman Street


All traffic originating from internal zones south of the Basin Reserve and east of Tasman Street


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4 Model�Development�

The model development process involves bringing together all sources of data and knowledge gained during the data collection stage. Network coding is done in the S-Paramics software package with constant reference to aerial photography, as built drawings (Inner City Bypass) and on street observations.

Bus routes, bus stops and timetables are coded into the modelled network as per published timetables.

In addition to the network coding, a number of parameters can be configured to calibrate the model operation. This section describes the model development and discusses the model parameters used.

4.1 Model�Periods�

S-Paramics micro-simulation models have been developed for the following peak periods:

� 07:00 to 10:00 (Weekday AM Peak period)

� 11:00 to 14:00 (Weekday Inter-peak period)

� 16:00 to 19:00 (Weekday PM Peak period)

Within these three peak periods the following peak hour periods have been identified from on-site observations and data collection:

� 08:00 to 09:00 (Weekday AM Peak hour)

� 12:00 to 13:00 (Weekday Inter-peak Peak hour)

� 17:00 to 18:00 (Weekday PM Peak hour)

These three peak period models have been calibrated / validated for the base year (2009) in order to provide a representative sample of origins and destinations within the study area.

The peak hour for each peak period has been fully calibrated / validated for the base year (2009) in order to provide a representative sample of origins and destinations within the study area. Further to this the pre-peak half hour (the half hour period before the peak hour period) for each model has been calibrated to journey time data to ensure the build up to the peak is also representative.


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4.2 Public�Transport�

To ensure that all bus routes and timetables were taken into account in the study area, the Wellington GIS based bus route database was obtained from the Greater Wellington Regional Council (GWRC). Using the software package ArcGIS, the bus routes within the study area were isolated via assessment of the spatial location of each stop. The routes assigned to these stops were then assessed individually to identify entry point locations and the ‘time at model’ for each timetabled service. Finally all common routes were grouped together and coded into the model with their associated timetables.

Bus stop dwell times were derived from data collected as part of the Golden Mile Capacity Assessment carried out by Opus International Consultants in 2006. As part of this study a number of bus stops along the ‘Golden Mile’ (Lambton Quay to Courtney Place) were surveyed. Using the observed dwell time information in this study, average dwell times for each peak period were derived, as seen in Table 4-1.

Table�4�1:�Bus�Stop�Dwell�Times�

Peak� Dwell�Time� Comment�

AM� 20 seconds Predominantly passengers alighting in the CBD

IP� 30 seconds Mixture of passengers boarding and alighting

PM� 40 seconds Predominantly passengers boarding in the CBD


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4.3 Network�Coding�

4.3.1 Routing�and�Cost�Factors�

The following model screenshot (Figure 4-1) indicates the major (red) and minor (blue) links used to control the predominant route choice within the model. In addition to this, links with cost factors adjusted above or below 1 have been highlighted with explanations below.

Figure�4�1:�Cost�Factor�Adjustments�

1. Adjustments have been made to cost factors here to discourage the use of ‘shortcutting’

from the Basin Reserve onto Tasman Street (2.0 on the minor link between the Basin and

Tasman Street) and also to encourage vehicles on Tasman Street to use Tasman Street and

reduce the shortcut onto the Basin Reserve.

2. A very high cost factor (10) has been applied to the available u-turn between Cambridge and

Kent. This has been used as it is much more likely that vehicles will travel around the Basin

Reserve than come off the Basin Reserve, u-turn then join it again. The reason for this u-turn

being in place is only to allow on-street parking to turn around.

1

2

3

4

5

6

7


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3. A cost factor (1.2) has been applied to Manners Street to take into account the major bus

stop on this link which discourages traffic to use this route in favour of Dixon Street.

4. Goa Street is a minor street between SH1 and Moxham Ave, and is not used often primarily

due to safety. Therefore a reasonably high cost factor (4) has been applied to these links.

5. It was observed that Webb Street was being used as an unrealistic alternative route, when

congestion increased on the Inner City Bypass. Therefore a cost factor has been applied to

discourage the use of this route.

6. Taranaki Street is a major north-south route through the CBD with 3 lanes in each direction

in most places. A cost factor of 0.8 has been applied to the northern half of Taranaki Street

to encourage the use of this route and promote its capacity in comparison with other north-

south alternatives.

7. This cost factor reduces the vehicles choosing this turn off from the motorway as per

surveyed traffic levels and due to delays in Hataitai Village.

4.3.2 Restrictions�

Vehicles heading northbound on the Inner City Bypass have moved into a separate matrix to allow the use of vehicle restrictions to control lane choice and route choice decisions. These are described below.


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�

Figure�4�2:�Lane�Choice�Restrictions

1. The observed lane choice behaviour on Victoria Street posed a challenge due to the early decisions necessary. To encourage modelled vehicles to make correct lane choice decisions, a restriction applying to all vehicles turning right onto the bypass has been coded on Victoria Street. This encourages traffic heading to the bypass to use the right hand lane from an early stage along Victoria Street.

2. The Inner City Bypass becomes extremely busy and slow moving during peak periods,

however signal coordination allows traffic to flow through the bypass. To stop modelled vehicles moving to less congested side roads and the back onto the bypass, restrictions were used to ban vehicles heading northbound on the bypass from turning off onto side roads.

3. Restrictions around the Basin Reserve influence correct lane choice behaviour for vehicles

circulating around towards the bypass and for vehicles exiting onto Adelaide Road.

4.3.3 Link�Speeds�

The following snapshot (Figure 4-3) indicates the link speeds used. The predominant methodology has been to use 45km/hr major links (red) for main routes throughout the model. This has been reduced slightly from the speed limit of 50km/hr to represent the fact that in a CBD network with a high number of traffic signals, it is unlikely that the speed limit will be reached frequently during

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1

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peak times. A 40km/hr link speed has been used for minor links (dark blue) in residential areas and 30/km/hr minor links (light blue) on inner-city side streets. Further adjustments beyond this methodology have been explained below.

Figure�4�3:�Manual�Link�Speed�Adjustment�Locations�

1. Due to the confined nature of the Mt Victoria Tunnel, vehicles tend to travel slowly especially in congested periods. Therefore the link speeds through the tunnel have been reduced to 30km/hr from the signposted speed of 50km/hr.

2. Due to the multiple circulating lane arrangement of the Basin Reserve ‘roundabout’, with

high level of lane changing, link speeds have been reduced to 35km/hr from the signposted 50km/hr.

3. This stretch of road is officially signposted at 70km/hr, however either side of this is

50km/hr. During peak periods, vehicles do not reach the signposted speed. Therefore the link speeds here have been set to 50km/hr.

4. At the intersection of Kilbirnie Crescent and SH1 heading westbound is a very difficult merge

which happens immediately following the signals. This creates a lot of congestion through this section of road, often blocking back to the intersection with Evans Bay Parade. In an

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3

4

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attempt to replicate this, low link speeds have been used through this section of the model, including a 20km/hr link speed at the merge point.

5. This section of the motorway is access restricted and has a signposted speed of 80km/hr.

This has been used as the modelled link speed in this area, with the exception of the segment through the Terrace Tunnel, where a slightly lower link speed has been used (60km/hr).


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4.4 Global�Parameters�

4.4.1 Modelled�Traffic�Behaviour�

The modelling package S-Paramics attempts to represent observed driver behaviour within the model through a number of parameters. Driver/vehicle characteristics are represented by the variables aggression and awareness. These factors influence a driver’s gap acceptance, car following, and lane changing characteristics.

The following driver behaviour parameters have been used in the Wellington CBD S-Paramics models:

� Aggression – sets the distribution of aggression used to assign an aggression characteristic to each entering vehicle. Aggression parameter used: x1

� Awareness – sets the distribution of driver awareness used to assign an awareness characteristic to each entering vehicle. Aggression parameter used: x1

� Mean Headway – describes the average or ‘target’ following time for moving vehicles (not in a queued state). Mean Headway parameter used: 1.5 sec – refer to section 4.4.3 for discussion on this parameter.

� Minimum Gap – describes the average or ‘target’ following distance for vehicles in a queued state. Minimum Gap parameter used: 1.6 m

4.4.2 Traffic�Assignment�

S-Paramics assigns traffic to the network according to routeing tables, which are influenced by:

� Link Cost - based on a function of time, distance and toll;

� Road Classification such as speed, hierarchy, etc;

� Driver Familiarity;

� Perturbation (stochastic) effects;

� Lane restrictions/closures; and

� Dynamic Feedback.

Dynamic assignment allows vehicles to re-route after a user-defined feedback period based on a user defined combination of the current and previous link costs. This attempts to replicate drivers knowledge of congestion during peak times and a willingness to change routes to avoid this congestion.


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The following traffic assignment parameters have been used in the Wellington CBD S-Paramics models:

� Generic Cost Equation (all vehicle types): 0.6T + 0.4D + 0.0P

� Feedback Interval: 2:00 mins

� Feedback Factor: 0.2

� Perturbation Method: Percentage

� Perturbation: 5.00 (all vehicle types)

� Familiarity: 50% for cars & 10% for heavy vehicles.

o Familiarity has been set low to replicate the predominant use of main roads and a low level of ‘rat-running’.

4.4.3 Mean�Headway�Discussion�

During model calibration it was discovered that the mean headway parameter showed a more representative level of congestion when set at 1.5 seconds. This is an increase from the default of 1.0 seconds.

The mean headway parameter acts as a target gap for vehicles to attempt to achieve when unconstrained by both congestion and the road environment. In addition to the road environment, influence from behavioural characteristics such as aggression also affects the actual modelled headway. This parameter applies to vehicles in a moving state. When vehicles encounter a queue, the mean headway parameter no longer applies and the minimum gap is becomes the predominant influence.

We have carried out a number of tests to examine the influence of this parameter. The results accompanying discussion are shown below.

A small Paramics model was build containing 1 unconstrained 2 way link with a speed of 45kph (to match category 1 in the Wellington model). 600 vehicles per hour were assigned to each direction along this link for a 2 hour duration. Using a loop the headway (gaps) were recorded over 10 runs.

It was decided that it would be inappropriate to look at ‘mean headway’ as problems occur when you’re looking at the upper end of values. Essentially this would require a decision as to at what headway constitutes a vehicle no longer being influenced/constrained by the leading vehicle and hence headways above this figure are excluded. Rough calculations based on the safe stopping distance of a vehicle travelling at 45kph and decelerating at 2mpss, indicate that this headway would be around 3 seconds. Due to the variability and assumptions needed to decide on an upper bound for a ‘mean’ calculation, it was deemed more appropriate to assess the headway using histograms.


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Histograms were created showing the number of occurrences of headways in bins of 0.1 seconds for both the modelled results and observed data from pneumatic tube counts.

The results showed that changing the mean headway parameter slightly shifted the distribution of modelled headways. We found that with the mean headway set to 1.0 seconds, the distribution showed a peak at between 1.0 and 1.2 seconds. Increasing this to 1.2 seconds the distribution peaked at around 1.2 to 1.5 seconds. Finally at 1.5 seconds the distribution peaked between 1.5 seconds and 1.8 seconds.

In almost all locations where tube count data enabled us to examine observed headways, the distributions seem to be peaking around 1.4 to 2.0 seconds. Therefore we consider a modelled headway of 1.5 seconds representative of observed conditions.

Figure 4-4 and Figure 4-5 show the observed headways recorded on site at Victoria Street and Willis Street. From these it can be seen that the peaks are closer to 2 seconds headway rather than 1.

Figure�4�4:�Histogram�of�Observed�Gaps�–�Victoria�Street�


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Figure�4�5:�Histogram�of�Observed�Gaps�–�Willis�Street�

As part of the testing requested we have compared the headway outputs based on the usage of either a 1 second, 1.2 second or 1.5 second headway setting within the model.

Figure 4-6 shows the comparative histograms associated with each of these headway settings.

Figure�4�6:�Distribution�of�Modelled�Headways�


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Figure 4-6 shows that as the mean headway parameter increases, the distribution of headways shift. When assessing these results it is important to take into account the operational characteristics of S-Paramics and where the mean headway parameter influences the modelled headway between vehicles. If a vehicle is slowing and entering a ‘queued state’, the minimum gap parameter is the predominant influence on headway. If a vehicle is not immediately behind another vehicle, then the modelled limitations on speed and acceleration, determined by the link speeds and the aggression parameter, are the predominant influence on headway. It is only when a vehicle is following another in a ‘moving state’ that mean headway becomes the predominant influence. It is the peaks in Figure 4-6 where this is occurring, and it is deemed that the peak distribution that represents the recorded data in the Wellington CBD most accurately is that for a mean headway of 1.5 seconds.


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5 Model�Calibration�

The base model has been calibrated and validated to accurately represent existing traffic conditions in the study area. This process provides more confidence in the model outputs regarding future traffic operations.

Model calibration is the process of changing the parameter values in a model in order to achieve agreement between simulation results and observed data. This process was undertaken by comparing modelled link counts and traffic behaviour to observed conditions from data collection carried out in February and March 2009.

The AM peak (0700 to 1000), IP peak (1100 to 1400) and PM peak (1600 to 1900) periods have been modelled in S-Paramics with the one hour peak periods calibrated to turning count and link count data for each of the modelled time periods.

Validation can be defined as a comparison of model output with observed data independent from the calibration process. Efforts have been made to validate the model to the observed on-site conditions as per the on site surveys carried out in February and March 2009.

The United Kingdom Design Manual for Roads and Bridges (DMRB) contains validation criteria that has used for the evaluation of the Wellington CBD S-Paramics models. This evaluation criteria is widely used throughout the world and forms the basis of a number of other model evaluation guidelines.

Currently the main New Zealand based model evaluation criteria is contained in the NZTA Economic Evaluation Manual (EEM). This criteria has been developed for strategic models and is not considered appropriate as a complete stand-alone evaluation guideline for micro-simulation models however reference to these in relation to each assessment criteria has been given. Specific guidelines are currently under development for micro-simulation models through the New Zealand Modelling User Group (NZMUGS), a sub-group of the IPENZ Transportation Group.

5.1 Statistical�Convergence�

Traditional traffic modelling software generally uses an assignment technique to split trips over a network based on the capacity of the links in the network and using a costing iteration until equilibrium is reached and traffic has been assigned appropriately throughout the network. These models are static and once equilibrium is reached, as measured by some convergence statistic, the results are fixed.

Unlike traditional traffic models, S-Paramics is a simulation package. It is not static and does not produce a single equilibrium answer. Alternatively, it seeks to model a range of different scenarios that, as accurately as possible, reflect scenarios that could occur in reality. Everyday on the road different situations arise and it is unlikely any two days are ever the same. A simulation package seeks to reproduce this.


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To create the randomness observed on the roads and to create a range of different scenarios, S-Paramics uses randomly generated numbers to assign characteristics to both driver behaviour and the release of vehicles onto the network.

It is the seed in S-Paramics that creates the random number streams used for the simulation and initiates two separate streams of random numbers. The first stream controls the release of vehicles onto the network. The second stream controls vehicle interactions (gap acceptance, hazard awareness, etc.) and driver behaviour within the network. By changing the seed you change both streams of random numbers and hence the release of vehicles onto the network and the interactions of these vehicles within the network. Each random seed in effect produces another simulation run.

In order to obtain results for validation purposes, each peak period has been run ten times. The seed numbers used for each run are shown in Table 5-1. The ten runs are then compared with each other to ensure they are operating within a similar range of results, eliminating the risk of unstable results for evaluation purposes. The results for validation are then based on the average of the 10 runs.

Table�5�1:�Seed�Numbers�

� AM�Peak�Model� Inter�Peak�Model� PM�Peak�Model�

Run�1� 1245822401 1245868617 1245845951

Run�2� 1245824382 1245870439 1245854966

Run�3� 1245826343 1245872259 1245848187

Run�4� 1245828316 1245874082 1245829912

Run�5� 1245830261 1245875913 1245850426

Run�6� 1245832201 1245877731 1245859524

Run�7� 1245834152 1245879554 1245836923

Run�8� 1245836119 1245881374 1245866404

Run�9� 1245838080 1245883201 1245841443

Run�10� 1245840031 1245885022 1245843692

As the validation results are an average comparison of 10 model runs, it is essential to investigate the stability of each model run. It is expected that variability will occur as per the previous discussion, however this variability should be within reasonable bounds and any runs where errors


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occurred should be eliminated from the analysis. Table 5-2, Table 5-3 and Table 5-4 summarise the variability of the 10 runs for each peak and hence the stability of the models.

Table�5�2:�AM�Peak�Model�Stability�

� Mean�Delay� Total�Distance�(m)�

Total�Number�of�Vehicles�

Mean�Speed�(kph)�

Mean 266 69811290 44311 21

Std Dev. 4 47026 17 0

Min 259 69721680 44281 21

Max 274 69882648 44326 22

Range 15 160968 45 1

CoV 0.01459 0.00067 0.00038 0.01449

Table�5�3:�IP�Peak�Model�Stability�




Mean 187 64445743 43136 29

Std Dev. 1 42137 13 0

Min 186 64364468 43117 29

Max 188 64496356 43160 29

Range 3 131888 43 0

CoV 0.00450 0.00065 0.00030 0.00438


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Table�5�4:�PM�Peak�Model�Stability�




Mean 235 75489817 54212 21

Std Dev. 5 50381 19 0

Min 226 75414064 54180 21

Max 245 75594096 54233 22

Range 18 180032 53 2

CoV 0.02085 0.00067 0.00034 0.02108

Table 5-2, Table 5-3 and Table 5-4 show that in all peaks the models are sufficiently stable with only a small amount of variation between runs. Comparing the results between each peak we can see that the coefficient of variation (CoV) indicates that the stability of each model is consistent with no one peak significantly more or less stable than another.


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5.2 Turning�Volumes�

Turn validation was carried out on all manual classified turning counts for the peak hour of operation (08:00 – 09:00, 12:00 – 13:00, 17:00 – 18:00) within each peak period (07:00 – 09:00, 11:00 – 13:00, 16:00 – 18:00).

Detailed tables of the turn validation for each peak can be seen in appendix A, in addition to these tables, charts of modelled vs. observed flows can be seen in section 7.1.4.

The following summary statistics for each peak show that industry accepted criteria has been sufficiently met, enabling the traffic demand to be considered ‘representative’.

5.2.1 GEH�

The GEH statistic was assessed for each count in the study area. The GEH tables are included within the observed verses modelled flow figures given in Appendix�A.

The GEH statistic is a form of the Chi-square measure of fit, and is defined as:

GEH = [( V2 - V1 )2 / ( 0.5 ( V1 + V2 )]

0.5

Where V1 = modelled flow (vehicle/ hour)

V2 = observed flow (vehicle/ hour)

The GEH figure is considered a more useful measure of performance for a model in a particular area than absolute or percentage differences in flows. A large percentage difference may relate to a small absolute difference on a lightly ‘trafficked’ link, and vice versa for links with greater flows, whereas the GEH statistic reduces the effects of both absolute and percentage differences.

The DMRB indicates that GEH should be less than 5 for 85% of flows. Further to this, the EEM indicates the following targets:

� At least 60% of individual link flows should have a GEH less than 5;

� At least 95% of individual link flows should have a GEH less than 10;

� All individual link flows should have GEH less than 12.

Table�5�5:�GEH�Results�

� AM�Peak�Hour� Inter�Peak�Hour� PM�Peak�Hour�

Less�than�5� 86% 94% 88%

Less�than�10� 100% 100% 99%

Greater�than�12� 0% 0% 0%


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The results in Table 5-5 show that both the DMRB and EEM criteria for GEH have been met in all peak models.

5.2.2 R�Squared�(Coefficient�of�Determination)�

The coefficient of determination indicates the ‘goodness of fit’ of modelled turn counts to observed count data as an overall summary statistic. An R2 of 1.00 indicates a perfect fit.

The DMRB guidelines state that the R2 should be 0.95 in the vicinity of the scheme and 0.90 everywhere else. The results shown in Table 5-6 are for the entire model and indicate a good statistical fit for all periods.

Table�5�6:�R2�Results�

AM�Peak�Hour� Inter�Peak�Hour� PM�Peak�Hour�

0.98 0.99 0.98

The results in Table 5-6 show that the DMRB criteria is exceeded in all modelled peaks.

5.2.3 RMSE�

The DMRB does not state a guideline for RMSE, however, the EEM recommends that the Root Mean Square Error (RMSE) be used to determine target precision levels of key traffic volumes from conventional transportation models. The equation for calculating the RMSE is given as:

� (Flow model – Flow observed)2 RMSE =

n – 1

�Flow observed

(

n )

where ‘n’ is the number of observations

The�Route�Mean�Square�Error�(RMSE)�was�calculated�for�the�turning�count�data�set�for�each�of�the�peak�periods.�The�RMSE�value�for�the�validated�period�was�found�to�be�within�the�EEM�guideline�specifying�an�

RMSE�less�than�30%.�Refer�to��

Table 5-7 for details of the RMSE statistics.

�

Table�5�7:�RMSE�Results�


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18 12 19

5.2.4 Turn�Count�Percentage�Differences�

In addition to the more advanced statistical measures such as GEH, R2 and RMSE, a number of guidelines recommend the assessment of percentage differences for turn/link counts.

The following table summarises the DMRB guidelines with respect to percentage differences.

�Table�5�8:�DMRB�Flow�Criteria�

Criteria� Flow� Requirement�

Within 15% 700vph < flow <2700vph 85% of cases

Within 100vph Flow < 700vph 85% of cases

Within 400vph Flow > 2700vph 85% of cases

Table 5-9 summarises the modelled turn count data with respect to the criteria shown in Table 5-8.

Table�5�9:�Modelled�Flow�Results�

� Counts�>�700� Within�Criteria� Counts�<�700� Within�Criteria�

AM 35 91% 206 99%

IP 27 100% 214 100%

PM 37 89% 204 99%

The results shown above are all within the DMRB guidelines.

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5.2.5 Turn�Count�Plots�

0

100

200

300

400

500

600

700

800

900

1000

0 100 200 300 400 500 600 700 800 900 1000

Mod

elle

d Fl

ow (v

eh/h

r)

Observed Flow (veh/hr)

PARAMICSScatter Plot of Modelled Turn Flows Versus Observed Turn Flows - AM Peak 2009

Y=X R2=0.98

Figure�5�1:�AM�Peak�Hour�Turn�Count�Scatter�Plot�

0

100

200

300

400

500

600

700

800

900

1000

0 100 200 300 400 500 600 700 800 900 1000

Mod

elle

d Fl

ow (v

eh/h

r)


PARAMICSScatter Plot of Modelled Turn Flows Versus Observed Turn Flows - IP Peak 2009

Y=X R2=0.99

Figure�5�2:�Inter�Peak�Hour�Turn�Count�Scatter�Plot�


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0

100

200

300

400

500

600

700

800

900

1000

0 100 200 300 400 500 600 700 800 900 1000

Mod

elle

d Fl

ow (v

eh/h

r)


PARAMICSScatter Plot of Modelled Turn Flows Versus Observed Turn Flows - PM Peak 2009

Y=X R2=0.98

Figure�5�3:�PM�Peak�Hour�Turn�Count�Scatter�Plot�


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5.3 Link�Counts�

As a secondary analysis of traffic demand and routing, link counts were compared throughout the model area in 61 separate locations. Comparison between modelled and observed link counts was done using the GEH statistic. The following table shows the results of this analysis.

Table�5�10:�Link�Count�GEH�Results�

� AM�Peak�Hour� Inter�Peak�Hour� PM�Peak�Hour�

Less�than�5� 90% 98% 92%

Less�than�10� 100% 100% 100%

Greater�than�12� 0% 0% 0%

Table 5-10 shows that modelled link counts are representative of observed numbers. The EEM turn/link count GEH criteria are being met in all three peaks.


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5.4 Screenlines�

Screenlines have been assessed to ensure that traffic entering and exiting the model from and to general directions is representative. These screenlines have been created by summing the total traffic volumes entering and exiting across these screenlines and GEH statistics calculated to compare observed and modelled volumes.

The following map shows the location of each screenline.

Figure�5�4:�Screenline�Locations�

Screenline 1 represents all traffic entering and exiting the model to/from the north, including the waterfront and the northern CBD area.

Screenline 2 represents all traffic entering and exiting the model to/from the south, including all suburbs in Wellington South.

1

3

2

4


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Screenline 3 represents all traffic heading eastbound and westbound in the centre of the model. This includes motorway traffic and local CBD trips.

Screenline 4 represents all traffic entering and exiting the CBD area of the model to/from all directions.

Both the DMRB and EEM reccomend that the GEH for the sum of directional screenline flows is less than 4 for most cases.

Table 5-11 shows the resulting GEH Statistics comparing modelled vs obsersved flows over each screenline.

Table�5�11:�Screenline�GEH�Results�


Screenline 1 SB 0.11 1.09 2.24

NB 0.08 0.48 0.49

Screenline 2 SB 3.64 1.35 3.31

NB 1.54 2.04 1.42

Screenline 3 EB 1.23 0.95 1.57

WB 2.02 4.83 3.82

Screenline 4 IN 0.21 1.48 0.93

OUT 0.20 0.76 4.19

Table 5-11 shows that almost all screenlines have a GEH much less than 4. In two instances the screenlines are marginally above 4, screenline 3 westbound in the IP Peak Hour and screenline 4 outbound in the PM Peak Hour. It is considered that despite these two screenlines, the models are overall representative with respect to screenlines due to the majority of values falling well within the criteria.

In addition to GEH values, screenlines have been assessed using percentage differences from the sum of counts. The results of this can be seen in Table 5-12.


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Table�5�12:�Screenline�Percentage�Difference�Results��


Screenline 1 SB 0% 2% 4%

NB 0% 1% 1%

Screenline 2 SB 8% 3% 5%

NB 3% 4% 3%

Screenline 3 EB 3% 2% 4%

WB 4% 11% 9%

Screenline 4 IN 0% 2% 1%

OUT 0% 1% 4%

Christchurch City Council Guidelines developed by BasePlus Ltd. Recommend that all screenlines are within 10%. The above results show that the Wellington CBD S-Paramics models meet this criteria with the exception of screenline 3 westbound in the interpeak period which is marginally over at 11%. As the peak periods with primary importance are the AM and PM, this difference is not considered to be of critical importance.


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5.5 Journey�Times�

Observed journey times have been compared with average modelled journey times in the peak hour period.

The DMRB guideline is for journey times to be within 15%. For journey time differences above 15%, the DMRB requirement is within 1 minute. The EEM discusses journey time results however does not specify a guideline for journey time comparisons.

The following table summarises the percentage difference between average observed and average modelled journey times (a negative number indicates that the modelled value is faster than the observed).

Table�5�13:�Peak�Hour�Journey�Time�Results�

Route AM�Peak�Hour� Inter�Peak�Hour� PM�Peak�Hour�

1 – Westbound -3% 3% -12%

1 – Eastbound -3% -7& -15%

2 – Willis Street 0% -11% -7%

3 – Victoria Street -11% -19% -6%

4 – Northbound 15% 1% -9%

4 – Southbound -4% -9% -16%

The results show that the majority of average modelled journey times are within 15% of observed values. In the two instances where the modelled journey time differs by more than 15%, the range of observed data was very large and hence the average was difficult to achieve however it has been ensured that the modelled trend of delay is consistent with the observed. In addition to this the actual difference for this journey time is 28 seconds and 27 seconds respectively. This is within the 1 minute criteria given in the DMRB for journey time differences greater than 15%.

Appendix B shows distance/time graphs for each journey time.

Note that route 5 northbound ends at the intersection of Taranaki Street and Wakefield Street and observed results were inclusive of delay at this intersection. As Wakefield Street is not included in the model area, a nominal intersection delay of 30 seconds was added to the average modelled results at this point to represent the average delay experienced at this intersection.


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5.6 Queue�Lengths�

Queue lengths were used as secondary criteria for calibration. The DMRB does not specify queue length guidelines, however mentions visual inspection in necessary.

Queue length data was recorded lane by lane at a number of intersections during the survey period. The average observed maximum queue lengths were compared with the average modelled maximum queue lengths over each peak hour.

Of the 102 queue lengths observed, Table 5-14 summarises the comparison with modelled queue lengths by assessing the percentage of average maximum queue length differences within the bounds specified.

Table�5�14:�Queue�Length�Results�


Less than +/- 5 veh 80% 89% 72%

Less than +/- 6 veh 85% 95% 79%

Less than +/- 7 veh 92% 95% 84%

Less than +/- 8 veh 95% 96% 88%

Less than +/- 9 veh 96% 98% 92%

The table above shows that the extent of queuing during the peak period is overall matching well with observed data.


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5.7 Visual�Validation�

In addition to calibration/validation criteria outlined in previous sections, visual validation is important to ensure the modelled network and congestion is visually comparable to on-site observations. This section examines some key areas of congestion in the modelled network.

The following snapshots of the network in both the AM and PM peak periods show the predominant areas of congestion. It is rare for significant congestion to develop in the inter-peak period.

5.7.1 AM�Peak�

Figure�5�5:�AM�Peak�Model�Snapshot�1�

1. Coming off the motorway onto Vivian Street is very busy and rarely slows for the entire

peak period.

2. Willis Street northbound is very busy during the AM peak period due to traffic heading

towards the Lambton Quay business district.

3. Coming around the Basin Reserve onto the bypass, traffic is busy during the AM peak

period, however it is not ‘highly congested’.

1

2

3

4


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4. Traffic through the Mt Victoria Tunnel heading towards the Basin Reserve is very congested

in the AM peak period, with queuing backing up through the tunnel.

Figure�5�6:�AM�Peak�Model�Snapshot�2�

5. During the AM peak the queue through the Mt Victoria Tunnel can often stretch all the way

through the tunnel and around the corner on the eastern side.

6. Due to the unsignalised right turn required to join the queue heading city bound, a large

amount of traffic often builds up around Hataitai, this causes vehicles to re-route by

heading away from the city to join SH1 in a less congested area.

7. The merge on SH1 directly after the Kilbirnie Street intersection causes congestion in this

area as heavy traffic results in vehicles travelling very slowly.

5 6

7


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5.7.2 PM�Peak�

Figure�5�7:�PM�Peak�Model�Snapshot�

1. Traffic heading into city is very busy throughout the peak period.

2. Traffic heading southbound on Victoria Street is highly congested throughout the PM peak.

This is due to the demand for traffic heading to the bypass and also traffic heading south

towards Aro Street and Brooklyn Road.

3. The inner city bypass in the PM peak is very congested and almost at a stand-still. Signal

coordination allows movement to occur at slow speeds. This congestion backs up through

the Basin Reserve.

1

2

3


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5.8 Peak�Shoulder�Periods�

Although full validation of peak shoulder periods has not been done, journey times have been assessed in the half hour pre peak shoulder to examine how representative these periods are of observed journey times.

Table 5-15 shows the percentage differences between observed and modelled journey times in the half hour pre peak (a negative value indicates the modelled result is faster than the observed).

Table�5�15:�Pre�Peak�Journey�Time�Differences�

Route AM�Pre�Peak� IP�Pre��Peak� PM�Pre�Peak�

1 – Westbound -10% 1% -10%

1 – Eastbound 0% 0% -4%

2 1% -4% -13%

3 -5% -19% -11%

4 – Northbound -3% -12% -12%

4 – Southbound -13% -11% -13%

The results shown in Table 5-15 indicate that the pre peak shoulder is validating well with respect to journey times. All differences in the AM and PM pre peak shoulders are within the DMRB requirement for journey times within 15%. One journey time in the inter peak pre peak shoulder have a difference greater than 15%; route 3 (-19%). The actual time difference on this route equates to 28 seconds. This difference is well within the DMRB guideline of a less than 1 minute difference for journey times greater than 15%.


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5.9 Signal�Timing�

Signal timing in a conventional ‘fixed-time’ model is an input parameter for each intersection, where by the modeller sets signal timings throughout the network. The Wellington CBD S-Paramics model utilises SCATS / Fuse adaptive signal timing and therefore SCATS signal personalities in conjunction with vehicle detections determine the signal timings whilst the simulation is running. This results in the simulated signal timings becoming an output of the simulation as opposed to an input parameter. These signal timings were compared with the timings that ran on-street on 4th March 2009, during the survey period.

No official calibration criteria exists for signal timings, however is has been ensured that the modelled timings are as close to observed values as possible. The following tables show the largest differences in each peak.

Table�5�16:�AM�Peak�Signal�Timing�Differences�

Intersection�ID� Description� Difference�

480 Willis Street / Ghuznee Street A -6%, B +6%

530 Vivian Street / Victoria Street A +8%, B -8%

1300 Wellington Road / Kilbirnie Street A +5%

430 Victoria Street / Dixon Street D -12%

510 Ghuznee Street / Taranaki Street A -6%, C +10%

550 Vivian Street / Taranaki Street A -6%

425 Dixon Street / Willis Street A +13%, B -6%, C -7%

650 Rugby Street / Adelaide Road A -6%, B +6%

Table�5�17:�IP�Peak�Signal�Timing�Differences�


480 Willis Street / Ghuznee Street A -%, D +5%

530 Vivian Street / Victoria Street A +10%, B -10%

450 Taranaki Street / Courtney Place / Dixon Street A +17%, B -13%, E -9%

470 Kent Terrace / Cambridge Terrace / Courtney CL -30s


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Place / Majoribanks Street

400 Boulcott Street / Willis Street / Manners Street A -6%

430 Victoria Street / Dixon Street CL -24s, A +7%, C+7%, D -14%

510 Ghuznee Street / Taranaki Street A +8%, C -8%

550 Vivian Street / Taranaki Street B -6%

1310 Wellington Road / Evans Bay Parade A +16%, C -15%, E -13%

425 Dixon Street / Willis Street B -5%

605 Karo Drive / Willis Street B -5%

Table�5�18:�PM�Peak�Signal�Timing�Differences�


480 Willis Street / Ghuznee Street A +12%, D -12%

530 Vivian Street / Victoria Street A -11%, B +11%

470 Kent Terrace / Cambridge Terrace / Courtney Place / Majoribanks Street

CL -24s

430 Victoria Street / Dixon Street D -12%

550 Vivian Street / Taranaki Street D +10%

1310 Wellington Road / Evans Bay Parade A +12%

650 Rugby Street / Adelaide Road A -10%, B +10%

Table 5-16, Table 5-17 and Table 5-18 show the largest signal timing differences and highlight where timings could possibly be out. The comparison observed data was signal timings observed on a single day (04/03/09), whilst count data used for the development of traffic demand was collected over a period of 2 months. Hence some differences are expected.


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6 Peer�Review�

During the development and validation of the Wellington CBD S-Paramics models, a peer review process was carried out by Aurecon.

Initial discussions during project scoping identified the need to carry out additional data collection including turning counts at more intersections in the CBD area and additional journey time runs.

Following model development and calibration, the model coding, model parameters, signal timings and validation results were reviewed. A number of adjustments were recommended and these were implemented prior to the final results being reported on.

The Aurecon Wellington CBD S-Paramics Model Audit Report (42773-001) recognises these models as being fit for purpose. A copy of this report can be found in Appendix E.


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7 Forecasting�

The process applied to develop future year forecast models for the Wellington CBD has been developed to create a basis for comparison of proposed road improvements around the Basin Reserve.

Significant challenges arise when developing future year models for CBD road networks; road network changes are frequent within the CBD area, and road improvements outside the CBD often have a large influence on the volume of traffic reaching the CBD.

Therefore, investigation has been done into the issues described above, as they relate to the Wellington CBD, and a strategy has been developed to ensure accurate forecast models are developed which are appropriate for the assessment of the Basin Reserve.

The following section outlines the methodology applied and results from the forecast models.

7.1 Methodology�

7.1.1 Future�Road�Network�

A number of changes are expected on the Wellington road network over the coming years. Some of these are changes to the State Highway network comprising; capacity improvements, interchange upgrades and possible new routes with Transmission Gully and the Kapiti Coast expressway. Changes to the local road network focus more heavily on public transport with a large number of bus lanes proposed by Wellington City Council.

Initial forecast year models were developed to include all road network changes influencing the CBD area that were either confirmed or highly likely to happen. This included the proposed CBD bus lanes as illustrated below in Figure 7-1. Bus lanes implemented by 2016 are shown in blue and 2026 are shown in green. The proposed Manners Mall bus link is also included in this scheme and changes the direction of a number of links around the north western corner of the model study area.


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Figure�7�1�:�Proposed�Wellington�CBD�Bus�Lanes�

The majority of the proposed bus lanes shown above do not affect capacity for general traffic as they are accommodated by removing on-street parking. However, in some locations where road reserve is limited, the proposals show reductions in intersection capacity. These bus lane designs are still in a preliminary stage and no detailed design / assessment has been carried out.

The resulting road network operation shown when modelling these bus lanes in their preliminary ‘concept’ designs was such that significant congestion was occurring due to capacity reduction on critical links such as Willis Street, Victoria Street and Taranaki Street. This congestion was at a level considered ‘unacceptable’ and significant refinement to the bus lane designs will be required prior to implementation. It was determined that it would not be possible to accurately assess the impacts of the proposed Basin Reserve scheme with other significant issues occurring on the network.

As agreed by the New Zealand Transport Agency and Wellington City Council, the future year ‘Do Minimum’ models that are appropriate for the assessment of the Basin Reserve scheme should only include the proposed bus lanes in the immediate vicinity of the Basin Reserve. This includes; Kent Terrace, Cambridge Terrace and Adelaide Road.

The modelled ‘Do Minimum’ road network for both 2016 and 2026 in SATURN and S-Paramics have been coded to reflect this. Any implications on traffic at the Basin Reserve associated with other proposed schemes yet to be finalised, will be tested as sensitivities to the final Basin Reserve scheme.


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7.1.2 Traffic�Growth�

A significant amount of work has been done in predicting traffic growth in the Wellington region with the development of the WTSM EMME/2 model. The WTSM model has a base year of 2006 and future years 2016 and 2026.

Following the development of the WSTM strategic model, a SATURN model has been developed of the Wellington area. The SATURN model also has a base year of 2006 and future years 2016 and 2026. The future year SATURN models disaggregate the demand from WTSM into a more detailed zone structure.

The Wellington CBD S-Paramics model has largely the same zone structure as the CBD area of the SATURN model, with only a small number of SATURN zones disaggregated into more specific areas.

To ensure that the forecasted traffic growth in the S-Paramics model is consistent with the SATURN model and the WTSM model, a difference matrix approach has been deemed the most appropriate method to apply traffic growth to the S-Paramics model. In this method, a matrix of ‘growth’ is added to the calibrated S-Paramics matrices to grow the traffic demand from 2009 to 2016 and to 2026 on a cell by cell basis.

However as the base year of the SATURN model is 2006 and the base year of the S-Paramics model is 2009, it is necessary to discount 3 years of growth from the difference matrix produced by SATURN. This will be taken into account by assessing the manual traffic count differences from those observed in 2006 during the development of the SATURN model with the manual traffic counts observed in 2009 during the development of the S-Paramics model. This 3 years of growth will be subtracted from the difference matrix with a sector based approach.

The main reasons for choosing a cell by cell difference matrix approach over a percentage increase sector based approach is; to take into account the different demand drivers for through trips as opposed to CBD origin/destination trips, and to include any wider area redistribution caused by increased congestion or specific route capacity increases/decreases highlighted by the SATURN model. Using a sector based approach, this detail is lost in averages over the sector.

Initial testing of traffic growth between 2006 and 2016/2026 was carried out using the Wellington City SATURN models. This involved isolating the CBD model area within the SATURN model and comparing the traffic demand and routing throughout the network between 2006 and 2016/2026. The modelled 2016/2026 network included all (Regional Land Transport Strategy) schemes assumed to be implemented in the future with the exception of the Basin Reserve improvements.

This initial analysis showed that a large amount of vehicles in the future year SATURN models were choosing different routes through the CBD than in 2006 due primarily to the addition of bus lanes and the planned tidal lane arrangement in the Terrace Tunnel. The affect of this re-routing results in entry and exit points into the CBD model area changing for a large number of trips. This complicates the process of forecasting growth within the S-Paramics models as the ‘growth’ on a number of trips is being disguised by the effects of re-routing due to the future changes to the network. Effectively a large amount of ‘negative growth’ is seen on one trip and a large amount of


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‘positive’ growth on another, where in reality these are the same trips, just choosing a different route.

As a result of this initial testing it was determined that a ‘common year for comparison’ was necessary to determine growth along with a separate assessment of trip re-routing. The 2006 SATURN model was re-coded to replicate the 2009 road network which is the base year of the S-Paramics models. By comparing the 2006 traffic demand and the 2016 traffic demand on this 2009 network; and then extracting traffic movements in the CBD model area it was possible to isolate the traffic growth in terms of number of vehicles travelling from one area to another.

It was then necessary to take into account the re-distribution of trips in the CBD area due to the network changes that are expected to occur. To do this traffic demand on the 2009 road network (without the future network changes) has been compared to the traffic demand on the 2016/2026 road network (with the network changes). Trip routes through the CBD where the entry/exit point has been affected due to these network changes has then been manually reassigned to the new entry/exit point in accordance with the redistribution being forecast by SATURN.

7.2 2016�and�2026�Traffic�Demand�

Table 7-1 and Table 7-2 summarise the future year traffic growth and Figure 7-2 shows traffic demand resulting from the methodology applied in section 7.1.2.

Table�7�1�:�Total�traffic�growth�from�2009�to�2026�

Total�Growth Growth�2009�to�2016� Growth�2016�to�2026�

AM Peak Hour (8:00am – 9:00am) 6.06% 10.84%

IP Peak Hour (12:00pm – 1:00pm) 6.34% 9.38%

PM Peak Hour (5:00pm – 6:00pm) 6.02% 9.12%

Table�7�2�:�Annual�traffic�growth�from�2009�to�2026�

Annual�Growth Growth�2009�to�2016� Growth�2016�to�2026�

AM Peak Hour (8:00am – 9:00am) 0.87% 1.08%

IP Peak Hour (12:00pm – 1:00pm) 0.91% 0.94%

PM Peak Hour (5:00pm – 6:00pm) 0.86% 0.91%


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0

5,000

10,000

15,000

20,000

25,000

2009 2016 2026

Traf

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eman

d�(p

eak�

hour

�tri

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Year

Wellington�CBD�Traffic�Demand�(2009�to�2026)

AM

IP

PM

Figure�7�2�:�Peak�hour�traffic�demand�2009�to�2026�

Figure 7-2 shows traffic demand increasing in the period 2009 to 2026. The growth to 2016 is comparably slower than between 2016 and 2026. This is due to proposed increases in the attractiveness of public transport taking an increased share of the growth in demand for movement from place to place up to 2016. Beyond 2016 it is expected that this growth in public transport usage will slow and lead to a greater rate in car traffic growth. This effect is supported by Greater Wellington Regional Councils predictions for growth in public transport usage.

7.3 2016�and�2026�Network�Operation�

The effects of the additional traffic in 2016 and 2026 have been modelled in the agreed ‘Do Minimum’ network and visually assessed along with analysis of journey times on key routes in the CBD.

7.3.1 Visual�Assessment�–�Do�Minimum�Models�

The visual assessment has shown that for the year 2016 the network is able to service the increase in traffic without significant detriment to delay. However, traffic demand in 2026 appears to exceed the capacity of parts of the network seen through significant increases in congestion on a number of key routes.

� Specific issues highlighted in the visual assessment of the 2016 and 2026 ‘Do Minimum’ models include;


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� The intersection of Taranaki Street / Buckle Street has insufficient capacity to cope with expected future demand. This becomes a significant issue in 2026 with significant queuing down Wallace Street in the AM peak for vehicles heading into the city and up the length of Taranaki Street in the PM peak for vehicles exiting the city. The queuing on Taranaki Street in the PM peak causes ‘knock-on’ effects on Ghuznee Street.

� Congestion on the Inner City Bypass in 2026 causing significant queuing around the Basin Reserve and affecting the ability of the north – south corridor to operate effectively.

� A reduction in the efficiency of the Basin Reserve resulting in queuing through the Mt Victoria Tunnel and onto Ruahine Street becoming more prevalent and lasting for longer. This also causes further reduction in the efficiency of the right turn from Taurima Street towards the Mt Victoria Tunnel, resulting in queuing around the Hataitai Village.

� Prolonged queuing through the Mt Victoria Tunnel and onto Ruahine Street making the route into the CBD less attractive leading to more vehicles choosing to use Evans Bay Parade. This reduces the efficiency of the Wellington Road / Evans Bay Parade / Cobham Drive intersection with higher demand for right turning movements.

� Willis Street in the AM peak and Victoria Street in the PM peak having difficulty to service the additional traffic.

7.3.2 Journey�Time�Comparisons�–�‘Do�Minimum’�Models�

Journey time comparisons between existing situation and the 2016 / 2026 ‘Do Minimum’ models for key routes through the CBD are shown below in Figure 7-3 to Figure 7-8.


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0

200

400

600

800

1000

1200

Base 2009 Do Minimum 2016 Do Minimum 2026

Ave

rage

�Jour

ney�

Tim

e�(s

)

SH1�Westbound�(Evans�Bay�Parade�to�Willis�Street)

AM

IP

PM

Figure�7�3�:�SH1�Westbound�Journey�Times�(2009�–�2026)�

0

50

100

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500


Ave

rage

�Jour

ney�

Tim

e�(s

)

SH1�Eastbound�(Willis�Street�to�Evans�Bay�Parade)

AM

IP

PM

Figure�7�4�:�SH1�Eastbound�Journey�Times�(2009�–�2026)�


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0

20

40

60

80

100

120


Ave

rage

�Jour

ney�

Tim

e�(s

)

Basin�Reserve�Northbound�(Adelaide�Road�to�Cambridge�Terrace)

AM

IP

PM

Figure�7�5�:�Basin�Reserve�Northbound�Journey�Times�(2009�–�2026)�

0

20

40

60

80

100

120

140


Ave

rage

�Jour

ney�

Tim

e�(s

)

Basin�Reserve�Southbound�(Kent�Terrace�to�Adelaide�Road)

AM

IP

PM

Figure�7�6�:�Basin�Reserve�Southbound�Journey�Times�(2009�–�2026)�


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0

20

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Ave

rage

�Jour

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Tim

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)

Taranaki�Northbound�(Webb�to�Wakefield)

AM

IP

PM

Figure�7�7�:�Taranaki�Street�Northbound�Journey�Times�(2009�–�2026)�

0

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100

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500


Ave

rage

�Jour

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Tim

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)

Taranaki�Southbound�(Wakefield�to�Webb)

AM

IP

PM

Figure�7�8�:�Taranaki�Street�Southbound�Journey�Times�(2009�–�2026)�


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The graphs shown in Figure 7-3 to Figure 7-8 validate what was seen in the visual assessment of the future year ‘Do Minimum’ networks.

SH1 journey times in the westbound and eastbound directions remain fairly similar to the existing situation in 2016. However 2026 shows significant increases in SH1 journey times with the greatest increase on the westbound route in the PM peak.

Travelling northbound from Adelaide Road to Cambridge Terrace through the Basin Reserve during the AM and PM peak periods significant increases are seen in both 2016 and 2026. The southbound route from Kent Terrace to Adelaide Road remains constant in the AM peak, however the PM peak shows a significant increase in journey time in 2026.

As previously mentioned, Taranaki Street experiences significant issues with future year traffic demand. Of particular concern is the southbound route in the PM peak where the average journey time is more than doubling in 2026.


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APPENDIX�A�

Turn�Validation�Data�

NO. ANODE BNODE CNODE COUNT COUNT COUNT MODELLED DIFFER- % Diff GEHHCV CARS TOTAL

Evan Bay Pde (S) LT Wellington (W) 1 608 610 603 78 78 91 -13 -16.79 1.42Evan Bay Pde (S) TH Evan Bay Pde (N) 2 608 604 609 172 172 173 -1 -0.81 0.11Evan Bay Pde (S) RT Cobham (E) 3 608 604 614 2 40 42 42 0 -0.95 0.06Cobham (E) LT Evan Bay Pde (S) 4 605 608 616 24 24 24 0 0.42 0.02Cobham (E) TH Wellington (W) 5 605 604 610 23 980 1003 893 110 11.00 3.58Cobham (E) RT Evan Bay Pde (N) 6 676 604 609 4 582 586 508 78 13.24 3.32Evan Bay Pde (N) LT Cobham (E) 7 609 614 606 1 264 265 265 0 -0.04 0.01Evan Bay Pde (N) TH Evan Bay Pde (S) 8 609 604 608 110 110 110 1 0.45 0.05Evan Bay Pde (N) RT Wellington (W) 9 609 604 610 21 21 19 2 10.48 0.49Wellington (W) LT Evan Bay Pde (N) 10 621 609 617 54 54 60 -6 -10.93 0.78Wellington (W) TH Cobham (E) 11 621 604 614 23 796 819 828 -9 -1.09 0.31Wellington (W) RT Evan Bay Pde (S) 12 610 604 608 150 150 105 45 30.07 3.99Kilbimia (S) LT Wellington (W) 13 600 667 581 206 206 195 11 5.44 0.79Kilbimia (S) TH Hanmilton (N) 14 600 585 586 194 194 172 22 11.39 1.63Kiilbinia (S) RT Wellington (E) 15 600 585 602 23 23 22 1 5.65 0.27Wellington (E) LT Kilbimie (S) 16 611 600 590 1 1 1 0 -10.00 0.10Wellington (E) TH Wellington (W) 17 611 585 667 22 948 970 890 80 8.28 2.63Wellington (E) RT Hanmilton (N) 18 602 585 586 1 135 136 113 23 16.91 2.06Hanmilton (N) LT Wellington (E) 19 586 585 602 1 100 101 91 10 9.70 1.00Halminton (N) TH Kilbimie (S) 20 586 585 600 85 85 75 10 11.53 1.09Hanmilton (N) RT Wellingotn (W) 21 586 585 667 23 23 13 10 45.22 2.47Wellington (W) LT Hanmilton (N) 22 601 585 586 12 12 30 -18 -153.33 4.00Wellington (W) TH Wellington (E) 23 601 585 602 22 837 859 880 -21 -2.47 0.72Wellington (W) RT Kilbimie (S) 24 667 585 600 4 179 183 156 27 14.97 2.11Wellington (E) TH Wellington (W) 25 599 596 597 22 991 1013 1068 -55 -5.44 1.71Wellington (E) RT Moxham (N) 26 599 596 598 30 30 29 1 2.00 0.11Moxham (N) LT Wellington (E) 27 598 599 581 1 1 6 -5 -500.00 2.67Moxham (N) RT Wellington (W) 28 598 596 597 11 11 45 -34 -310.00 6.44Wellington (W) LT Moxham (N) 29 578 597 598 16 16 31 -15 -94.38 3.11Wellinigton (W) TH Wellington (W) 30 597 596 599 26 1021 1047 1060 -13 -1.21 0.39Wellington (SW) LT Ruahine (N) 31 580 583 576 156 156 103 53 34.10 4.68Welliington (SW) RT Wellington (E) 32 580 579 578 1 132 133 162 -29 -22.03 2.41Wellington (E) LT Wellington (SW) 33 582 580 584 112 112 131 -19 -16.79 1.71Wellington (E) RT Ruahine (N) 34 582 579 583 22 879 901 982 -81 -8.99 2.64Ruahine (N) LT Wellington (E) 35 576 578 597 25 832 857 929 -72 -8.35 2.40Ruahine (N) RT Wellington (SW) 36 592 579 580 3 103 106 117 -11 -10.47 1.05Moxham (S) LT Goa (W) 37 565 563 504 58 58 50 8 13.28 1.05Moxham (S) TH Moxham (N) 38 565 563 540 1 239 240 179 61 25.46 4.22Moxham (S) RT Goa (E) 39 565 563 601z 9 9 12 -3 -30.00 0.84Goa (E) LT Moxham (S) 40 601z 563 565 11 11 35 -24 -215.45 4.96Goa (E) TH Goa (W) 41 601z 563 504 7 7 0 7 100.00 3.74Goa (E) RT Moxham (N) 42 601z 563 540 14 14 65 -51 -366.43 8.15Moxham (N) LT Goa (E) 43 540 563 601z 9 9 25 -16 -178.89 3.90Moxham (N) TH Moxham (S) 44 540 563 565 2 153 155 82 73 46.97 6.68Moxham (N) RT Goa (W) 45 540 563 504 32 32 15 17 52.19 3.43Goa (W) LT Moxham (N) 46 504 563 540 1 17 18 5 13 72.78 3.87Goa (W) TH Goa (E) 47 504 563 601z 4 4 3 1 22.50 0.48Goa (W) RT Moxham (S) 48 504 563 565 5 5 0 5 100.00 3.16Moxham (S) LT Taurima (W) 49 683 511 512 166 166 72 94 56.57 8.61Moxham (S) TH Hataitai (N) 50 683 511 541 1 89 90 176 -86 -95.78 7.47Hataitai (N) TH Moxham (S) 51 541 511 683 1 116 117 105 12 10.43 1.16Hataitai (N) RT Taurima (W) 52 541 511 512 1 228 229 275 -46 -20.00 2.89Taurima (W) LT Hataitai (N) 53 512 511 541 78 78 69 9 11.28 1.03Taurima (W) RT Moxham (S) 54 512 511 683 1 22 23 17 6 24.35 1.25Ruahine (S) TH Mt Victoria Tunl (W) 55 88 515 182 22 1063 1085 1124 -39 -3.61 1.18Taurima (E) LT Ruahine (S) 56 513 516 515 14 14 36 -22 -159.29 4.45Taurima (E) RT Mt Victoria Tunl (W) 57 513 514 182 399 399 313 86 21.45 4.54Mt Victoria Tunl (W) LT Taurima (W) 58 501 182 513 1 99 100 87 14 13.50 1.40Mt Victorial Tunl (W) TH Ruahine (S) 59 501 182 515 28 952 980 965 15 1.52 0.48Aldelaide (S) LT Rugby (W) 60 170 171 169 16 964 980 1080 -100 -10.23 3.13Rugby (E) LT Adelaide (S) 61 168 665 666 15 425 440 504 -64 -14.64 2.96Rugby (E) TH Rugby (W) 62 167 168 169 22 1694 1716 1646 70 4.10 1.72Paterson (E) LT Dufferin (S) 63 166 159 165 22 1437 1459 1427 32 2.21 0.85Kent (N) LT Paterson (E) 64 157 164 158 29 1025 1054 1047 7 0.65 0.21Kent (N) TH Dufferin (S) 65 157 165 161 15 682 697 750 -53 -7.59 1.97Kent (N) LT Dufferin (S) 66 151 155 162 44 1707 1751 1743 8 0.45 0.19Buckle (W) LT Cambridge (N) 67 11 153 152 6 951 957 987 -30 -3.10 0.95Buckle (W) TH Dufferin (E) 68 11 154 155 0 10 -10 0.00 0.00Dufferen (W) LT Hania St 69 162 163 659z 28 28 10.6 17.4 62.14 3.96Dufferen (W) TH Ellice St 70 162 163 89 155 155 131.7 23.3 15.03 1.95Hania St (N) TH Dufferin St 71 659z 163 249 41 41 51.7 -10.7 -26.10 1.57Ignore This Row 89 163 249 128.4Ellice St (E) LT Dufferin St 72 89 175 157 100 100 137.1 -37.1 -37.10 3.41Sussex (S) LT Buckle (W) 73 10 174z 342 25 1542 1567 1729 -162 -10.33 3.99Suxxex (S) RT Buckle (E) 74 216 10 11 13 1189 1202 978 224 18.61 6.78Rugby (E) TH Rugby (W) 75 169 172 174 29 29 3 26 90.34 6.57Rugby (W) LT Sussex (N) 76 7 174 173 61 61 66 -5 -8.52 0.65Cambridge (S) TH Cambridge (N) 77 655 104 103 7 922 929 960 -31 -3.33 1.01Cambridge (S) RT Pirie (E) 78 140 104 105 39 39 66 -27 -68.72 3.70Pirie (E) LT Kent (S) 79 105 104 143 59 59 30 30 50.00 4.43Pirie (E) RT Kent (N) 80 105 104 103 64 64 20 44 69.22 6.85Kent (N) LT Pirie (E) 81 141 104 105 43 43 24 19 45.12 3.36Kent (N) TH Kent (S) 82 141 104 143 18 778 796 844 -48 -6.02 1.67Vivian (W) LT Cambridge (N) 83 621z 104 103 6 68 74 38 36 48.65 4.81Vivian (W) TH Pirie (E) 84 621z 104 105 2 71 73 80 -7 -9.45 0.79Vivian (W) RT Kent (S) 85 621z 104 143 25 1035 1060 1017 43 4.04 1.33Cambridge (S) LT Courtenay (W) 86 656 490 487 1 212 213 202 11 4.98 0.74Cambridge (S) TH Cambridge (N) 87 492 484 491 8 778 786 705 81 10.36 2.98Cambridge (S) RT Majoribanks (E) 88 492 484 489 73 73 52 21 28.22 2.60Majoribanks (E) LT Kent (S) 89 489 484 493 1 28 29 22 7 22.76 1.30Majoribanks (E) TH Courtenay (W) 90 489 484 490 1 100 101 113 -12 -11.78 1.15Majoribanks (E) RT Cambridge (N) 91 489 484 491 1 341 342 346 -4 -1.11 0.20Kent (N) LT Majoribanks (E) 92 494 484 489 1 139 140 140 0 -0.14 0.02Kent (N) TH Kent (S) 93 494 484 493 15 763 778 850 -72 -9.19 2.51Kent (N) RT Courtenay (W) 94 494 484 490 1 103 104 129 -25 -23.75 2.29Courtenay (W) LT Cambridge (N) 95 490 491 368x 26 26 62 -36 -137.69 5.40Courtenay (W) TH Majoribanks (E) 96 490 484 489 1 37 38 61 -23 -60.79 3.28Courtenay (W) RT Kent (S) 97 490 484 493 2 81 83 101 -18 -21.08 1.83Tasman (S) LT Buckle (W) 98 186 8 368 139 139 124 16 11.15 1.35Tasman (S) TH Tory (N) 99 186 8 139z 135 135 74 61 45.33 5.99Buckle (E) LT Tasman (S) 100 342 8 186 0 0 0 0 0.00 0.00Buckle (E) TH Buckle (W) 101 342 8 368 25 1526 1551 1595 -44 -2.82 1.10Buckle (E) RT Tory (N) 102 342 8 139z 1 134 135 139 -4 -2.74 0.32Tory (N) TH Tasman (S) 103 139z 8 186 169 169 199 -30 -17.81 2.22Tory (N) RT Buckle (W) 104 139z 8 368 8 158 166 138 28 16.75 2.25Tory (S) TH Tory (N) 105 266 102 101 150 150 169 -19 -12.60 1.50Tory (S) RT Vivian (E) 106 266 102 621z 1 53 54 13 41 75.37 7.02Tory (N) LT Vivian (E) 107 101 102 621z 56 56 52 4 7.68 0.59Tory (N) TH Tory (S) 108 101 102 266 6 216 222 229 -7 -3.33 0.49Vivian (W) LT Tory (N) 109 341z 102 101 1 160 161 160 1 0.50 0.06Vivian (W) TH Vivian (E) 110 341z 102 621z 25 1119 1144 1069 75 6.54 2.25Vivian (W) RT Tory (S) 111 341z 102 266 2 146 148 176 -28 -19.05 2.21Tory (S) LT Courtenay (W) 112 500 271 496 81 81 129 -48 -59.14 4.68Tory (S) TH Tory (N) 113 500 271 497 206 206 105 101 49.08 8.11Tory (S) RT Courtenay (E) 114 500 271 270 23 23 76 -53 -229.13 7.50Courtenay (E) LT Tory (S) 115 270 271 500 1 40 41 57 -16 -38.05 2.23Courtenay (E) TH Courtenay (W) 116 270 271 496 275 275 337 -62 -22.36 3.52Courtenay (E) RT Tory (N) 117 270 271 497 8 8 19 -11 -131.25 2.88Tory (N) LT Courtenay (E) 118 497 271 270 13 13 7 6 45.38 1.86Tory (N) TH Tory (S) 119 497 271 500 171 171 151 20 11.58 1.56Tory (N) RT Courtenay (W) 120 497 271 496 14 14 31 -17 -123.57 3.64Courtenay (W) LT Tory (N) 121 496 271 497 35 35 62 -27 -78.00 3.91Courtenay (W) TH Courtenay (E) 122 496 271 270 162 162 234 -72 -44.44 5.12Courtenay (W) RT Tory (S) 123 496 271 500 1 61 62 61 1 2.26 0.18Taranaki (S) LT Arthur (W) 124 364y 9 629y 1 267 268 317 -49 -18.25 2.86Taranaki (S) TH Taranaki (N) 125 364y 9 674 6 410 416 532 -116 -27.91 5.33Buckle (E) LT Taranaki (S) 126 13 9 14 3 125 128 120 8 6.02 0.69Ignore This Row 13 9 364y 5Buckle (E) TH Arthur (W) 127 13 9 629y 28 1386 1414 1495 -81 -5.70 2.11Buckle (E) RT Taranaki (N) 128 630y 9 674 4 371 375 271 104 27.68 5.77Taranaki (N) TH Taranaki (S) 129 360z 9 364y 10 531 541 610 -69 -12.79 2.88Ignore This Row 360z 9 14 577Taranaki (N) RT Arthur (W) 130 674 9 629y 4 99 103 56 47 46.02 5.32Taranaki (S) LT Abel Smith (W) 131 353 50 232 79 79 38 41 51.77 5.35Taranaki (S) TH Taranaki (N) 132 353 50 636 6 737 743 781 -38 -5.05 1.36

Turn Flow Comparison: 8:00-9:00 AM Period

2/11/2009 12:28 p.m.

NO. ANODE BNODE CNODE COUNT COUNT COUNT MODELLED DIFFER- % Diff GEHTaranaki (N) TH Taranaki (S) 133 636 50 353 11 600 611 676 -65 -10.70 2.58Taranaki (N) RT Abel Smith (W) 134 636 50 232 1 69 70 47 23 33.43 3.06Abel Smith (W) LT Taranaki (N) 135 232 50 636 2 85 87 85 2 2.07 0.19Taranaki (S) TH Taranaki (N) 136 132 117 620z 6 735 741 812 -71 -9.60 2.55Taranaki (S) RT Vivian (E) 137 123 117 134 2 121 123 92 31 25.04 2.97Taranaki (N) LT Vivian (E) 138 620z 117 134 7 313 320 333 -13 -4.13 0.73Taranaki (N) TH Taranaki (S) 139 620z 117 123 9 354 363 404 -41 -11.16 2.07Vivian (W) LT Taranaki (S) 140 358z 117 620z 4 116 120 71 49 40.75 5.00Vivian (W) TH Vivian (E) 141 358z 117 134 19 1084 1103 980 123 11.14 3.81Vivian (W) RT Taranaki (S) 142 653 117 123 3 363 366 371 -5 -1.48 0.28Taranaki (S) LT Ghuznee (W) 143 228 99 137 245 245 196 49 19.84 3.27Taranaki (S) TH Taranaki (N) 144 228 99 638 10 616 626 650 -24 -3.82 0.95Taranaki (N) TH Taranaki (S) 145 638 99 228 10 468 478 464 14 2.91 0.64Taranaki (N) RT Ghuznee (W) 146 638 99 137 3 80 83 78 5 6.14 0.57Ghuznee (W) LT Taranaki (N) 147 137 99 638 5 227 232 252 -20 -8.75 1.30Ghuznee (W) RT Taranaki (S) 148 137 99 228 6 403 409 354 56 13.57 2.84Taranaki (S) LT Dixon (W) 149 199 82z 325 10 117 127 102 25 20.00 2.38Taranaki (S) TH Taranaki (N) 150 199 82z 287 5 588 593 607 -14 -2.34 0.57Taranaki (S) RT Courtenay (E) 151 339z 82z 273 124 124 154 -30 -24.52 2.58Courtenay (E) LT Taranaki (S) 152 273 82z 339z 136 136 142 -6 -4.63 0.53Courtenay (E) TH Dixon (W) 153 273 82z 325 1 202 203 328 -125 -61.53 7.67Courtenay (E) RT Taranaki (N) 154 273 82z 287 28 28 25 3 9.64 0.52Taranaki (N) LT Courtenay (E) 155 287 82z 273 73 73 65 8 10.96 0.96Taranaki (N) TH Taranaki (S) 156 287 82z 339z 11 420 431 366 65 15.08 3.26Taranaki (N) RT Dixon (W) 157 287 82z 325 49 49 47 2 4.90 0.35Manner (W) LT Taranaki (N) 158 297 82z 287 1 24 25 26 -1 -5.60 0.28Manner (W) TH Courtenay (E) 159 297 82z 273 2 61 63 129 -66 -105.08 6.75Manner (W) RT Taranaki (S) 160 297 82z 339z 2 44 46 47 -1 -2.83 0.19Cuba(S) LT Karo (W) 161 19 51 361 1 77 78 86 -8 -10.51 0.90Cuba (S) TH Cuba (N) 162 19 51 49 2 120 122 92 30 24.51 2.89Karo (E) LT Cuba (S) 163 629y 51 19 1 14 15 32 -17 -115.33 3.56Karo (E) TH Karo (W) 164 629y 51 361 37 1800 1837 1765 72 3.91 1.69Karo (E) RT Cuba (N) 165 629y 51 49 60 60 69 -9 -14.17 1.06Cuba (N) TH Cuba (S) 166 49 51 19 3 54 57 23 34 59.47 5.36Cuba (N) RT Karo (W) 167 49 51 361 1 26 27 16 11 41.48 2.42Karo (SE) LT Victoria (S) 168 360 362 363 2 107 109 82 27 24.86 2.77Karo (SE) TH Karo (NW) 169 360 357y 366y 21 1747 1768 1789 -21 -1.17 0.49Ignore This Row 362 357y 357 1461Victoria (N) TH Victoria (S) 170 29 358 357y 36 434 470 521 -51 -10.87 2.30Victoria (N) RT Karo (NW) 171 29 358 357 3 232 235 140 95 40.51 6.95Victoria (N) LT Vivian (E) 172 628 106 251 138 138 156 -18 -12.83 1.46Victoria (N) TH Victoria (S) 173 628 106 336 18 361 379 398 -19 -5.12 0.98Vivian (W) LT Victoria (N) 174 52z 115 139 70 70 103 -33 -47.71 3.59Vivian (W) TH Vivian (E) 175 115 106 251 25 1545 1570 1262 309 19.65 8.20Vivian (W) RT Victoria (S) 176 115 106 336 10 402 412 323 90 21.72 4.67Victoria (SW) LT Ghuznee (NW) 177 359z 94 652 1 1 3 -2 -190.00 1.36Victoria (SW) TH Victoria (NE) 178 359z 94 365 61 61 18 43 70.49 6.84Victoria (SW) RT Ghuznee (SE) 179 359z 94 96 1 8 9 71 -62 -683.33 9.75Ghuznee (SE) LT Victoria (SW) 180 364 94 359z 1 81 82 58 24 29.51 2.89Ghuznee (SE) TH Ghuznee (NW) 181 364 94 652 1 129 130 99 31 24.08 2.93Ghuznee (SE) RT Victoria (NE) 182 96 94 365 1 50 51 27 24 46.86 3.82Victoria (NE) LT Ghuznee (SE) 183 82 94 96 4 82 86 117 -31 -35.81 3.06Victoria (NE) TH Victoria (SW) 184 82 94 359z 6 267 273 277 -4 -1.47 0.24Victoria (NE) RT Ghuznee (NW) 185 365 94 652 3 33 36 66 -30 -83.33 4.20Ghuznee (NW) LT Victoria (NE) 186 652 94 365 1 76 77 53 24 30.91 2.95Ghuznee (NW) TH Ghuznee (SE) 187 652 94 96 496 496 536 -40 -7.98 1.74Ghuznee (NW) RT Victoria (SW) 188 652 94 359z 11 348 359 292 67 18.75 3.73Victoria (SW) LT Dixon (NW) 189 200 279 79 1 80 81 84 -3 -3.83 0.34Victoria (SW) TH Victoria (NE) 190 200 279 366w 1 42 43 17 26 60.00 4.70Dixon (SE) LT Victoria (SW) 191 81 279 200 1 78 79 60 19 24.18 2.29Dixon (SE) TH Dixon (NW) 192 81 279 79 251 251 269 -18 -6.97 1.09Dixon (SE) RT Victoria (NE) 193 81 279 366w 8 115 123 194 -71 -57.72 5.64Victoria (NE) TH Victoria (SW) 194 294 279 200 15 478 493 464 29 5.86 1.32Victoria (NE) RT Dixon (NW) 195 366w 279 79 2 102 104 107 -3 -3.17 0.32Manners (S) TH Manner (N) 196 343y 308 364x 10 110 120 215 -95 -78.83 7.31Victoria (N) TH Victoria (S) 197 309 342z 312 595 595 547 48 8.10 2.02Victoria (S) RT Manners (N) 198 309 342z 308 4 140 144 116 28 19.31 2.44Willis (SW) LT Abel Smith (NW) 199 38 43 206 1 109 110 97 13 11.82 1.28Willis (SW) TH Wellington Urban Mway 200 38 43 356 12 455 467 410 57 12.21 2.72Willis (SW) TH Willis (NE) 201 38 43 337 22 613 635 585 50 7.91 2.03Karo (SE) LT Abel Smith (NW) 202 367 43 206 153 153 146 7 4.77 0.60Karo (SE) TH Wellington Urban Mway 203 367 43 356 23 1462 1485 1426 59 4.00 1.56Karo (SE) RT Willis (NE) 204 357 43 337 5 364 369 361 8 2.20 0.42Abel Smith (NW) LT Wellington Urban Mway 205 206 43 356 11 11 11 0 0.91 0.03Abel Smith (NW) TH Willis (NE) 206 206 43 337 23 23 48 -25 -108.26 4.18Willis (S) TH Willis (N) 207 178 28 36 27 641 668 641 27 4.09 1.07Webb (E) LT Willis (S) 208 267z 28 178 22 261 283 331 -48 -16.86 2.72Webb (E) RT Willis (N) 209 27 28 36 6 385 391 339 52 13.27 2.72Willis (S) LT Aro (W) 210 28 36 39 210 210 234 -24 -11.57 1.63Willis (S) TH Willis (N) 211 28 36 41 33 816 849 746 103 12.13 3.65Aro (W) LT Willis (N) 212 39 41 38 326 326 327 -1 -0.31 0.06Willis (S) TH Willis (N) 213 260 52z 357z 18 653 671 659.7 11.3 1.68 0.44Willis (S) RT Vivian (E) 214 260 52z 115 5 347 352 344.1 7.9 2.24 0.42Vivan (W) LT Willis (N) 215 356z 357z 256 98 98 60.1 37.9 38.67 4.26Vivian (W) TH Vivian (E) 216 356z 52z 115 30 1639 1669 1342.1 326.9 19.59 8.42Willis (SW) LT Ghuzness (NW) 217 73 67 68 6 173 179 160 19 10.61 1.46Willis (SW) TH Willis (NE) 218 73 67 303 7 449 456 494.3 -38.3 -8.40 1.76Willis (SW) RT Ghuzness (NE) 219 73 67 652 2 110 112 47.4 64.6 57.68 7.24Ghuznee (NE) TH Ghuznee (NW) 220 652 67 68 137 137 143.4 -6.4 -4.67 0.54Ghuznee (NE) RT Willis (NE) 221 652 67 303 19 19 26.5 -7.5 -39.47 1.57Willis (NE) LT Ghuznee (SE) 222 303 67 652 1 194 195 180.8 14.2 7.28 1.04Willis (NE) RT Ghuznee (NW) 223 303 67 68 123 123 142.6 -19.6 -15.93 1.70Ghuznee (NW) LT Willis (NE) 224 68 67 303 19 19 18.2 0.8 4.21 0.19Ghuznee (NW) TH Ghuzness (SE) 225 68 67 652 12 610 622 647.6 -25.6 -4.12 1.02Willis (SW) LT Dixon (NW) 226 317 79 296z 34 34 36.5 -2.5 -7.35 0.42Willis (SW) TH Willis (NE) 227 317 79 319 13 433 446 521.3 -75.3 -16.88 3.42Dixon (SE) LT Willis (SW) 228 279 79 317 1 113 114 117.6 -3.6 -3.16 0.33Dixon (SE) TH Dixon (NW) 229 279 79 296z 47 47 128.2 -81.2 -172.77 8.68Dixon (SE) RT Willis (NE) 230 279 79 319 333 333 216.8 116.2 34.89 7.01Willis (NE) TH Willis (SW) 231 319 79 317 4 204 208 197.3 10.7 5.14 0.75Willis (NE) RT Dixon (NW) 232 319 79 296z 0 1.2 -1.2 0.00 0.00Dixon (NW) LT Willis (NE) 233 296z 79 319 29 29 77.9 -48.9 -168.62 6.69Dixon (NW) RT Willis (SW) 234 296z 79 317 0 0.4 -0.4 0.00 0.00Willis (SW) LT Manners (NW) 235 297z 301 315 4 334 338 313.6 24.4 7.22 1.35Willis (SW) TH Willis (NE) 236 297z 301 313 14 460 474 464.2 9.8 2.07 0.45Manners (SE) LT Willis (SW) 237 343z 301 297z 1 1 9.6 -8.6 -860.00 3.74Manners (SE) TH Manners (NW) 238 343z 301 315 1 174 175 147.1 27.9 15.94 2.20Manners (SE) RT Willis (NE) 239 343z 301 313 6 79 85 175.7 -90.7 -106.71 7.94Manners (NW) LT Willis (NE) 240 315 301 313 6 193 199 214.6 -15.6 -7.84 1.08Manners (NW) RT Willis (SW) 241 315 301 297z 4 172 176 162.2 13.8 7.84 1.06

Total no. of counts 241 Total % R2

Summation observed flows 74025 207 86% 0.98Summation (modelled - flows)2 711789 241 100%% RMSE 18 0 0%

241 0%Total

GEH SummaryGEH <5

GEH <10GEH >12

2/11/2009 12:28 p.m.


Evan Bay Pde (S) LT Wellington (W) 1 608 610 603 3 110 113 112 2 1.33 0.14Evan Bay Pde (S) TH Evan Bay Pde (N) 2 608 604 609 4 97 101 98 3 3.37 0.34Evan Bay Pde (S) RT Cobham (E) 3 608 604 614 15 15 15 0 -0.67 0.03Cobham (E) LT Evan Bay Pde (S) 4 605 608 616 20 20 20 0 1.00 0.04Cobham (E) TH Wellington (W) 5 605 604 610 45 867 912 908 4 0.47 0.14Cobham (E) RT Evan Bay Pde (N) 6 676 604 609 4 156 160 161 -1 -0.50 0.06Evan Bay Pde (N) LT Cobham (E) 7 609 614 606 2 225 227 227 0 -0.09 0.01Evan Bay Pde (N) TH Evan Bay Pde (S) 8 609 604 608 3 109 112 113 -1 -0.54 0.06Evan Bay Pde (N) RT Wellington (W) 9 609 604 610 54 54 52 2 2.96 0.22Wellington (W) LT Evan Bay Pde (N) 10 621 609 617 37 37 38 -1 -3.51 0.21Wellington (W) TH Cobham (E) 11 621 604 614 30 945 975 1005 -30 -3.08 0.95Wellington (W) RT Evan Bay Pde (S) 12 610 604 608 103 103 112 -9 -8.74 0.87Kilbimia (S) LT Wellington (W) 13 600 667 581 2 238 240 214 26 10.92 1.74Kilbimia (S) TH Hanmilton (N) 14 600 585 586 48 48 64 -16 -33.75 2.16Kiilbinia (S) RT Wellington (E) 15 600 585 602 1 15 16 14 2 13.13 0.54Wellington (E) LT Kilbimie (S) 16 611 600 590 9 9 9 0 0.00 0.00Wellington (E) TH Wellington (W) 17 611 585 667 47 935 982 1028 -46 -4.68 1.45Wellington (E) RT Hanmilton (N) 18 602 585 586 1 86 87 40 48 54.60 5.97Hanmilton (N) LT Wellington (E) 19 586 585 602 65 65 5 60 92.92 10.24Halminton (N) TH Kilbimie (S) 20 586 585 600 1 64 65 64 1 1.38 0.11Hanmilton (N) RT Wellingotn (W) 21 586 585 667 9 9 5 5 50.00 1.73Wellington (W) LT Hanmilton (N) 22 601 585 586 34 34 25 9 25.29 1.58Wellington (W) TH Wellington (E) 23 601 585 602 29 1014 1043 1135 -92 -8.83 2.79Wellington (W) RT Kilbimie (S) 24 667 585 600 59 59 63 -4 -5.93 0.45Wellington (E) TH Wellington (W) 25 599 596 597 49 1182 1231 1221 10 0.81 0.29Wellington (E) RT Moxham (N) 26 599 596 598 5 5 27 -22 -448.00 5.57Moxham (N) LT Wellington (E) 27 598 599 581 5 5 4 1 12.00 0.28Moxham (N) RT Wellington (W) 28 598 596 597 4 4 20 -16 -395.00 4.58Wellington (W) LT Moxham (N) 29 578 597 598 8 8 13 -5 -66.25 1.62Wellinigton (W) TH Wellington (W) 30 597 596 599 29 1103 1132 1217 -85 -7.54 2.49Wellington (SW) LT Ruahine (N) 31 580 583 576 4 57 61 61 0 -0.33 0.03Welliington (SW) RT Wellington (E) 32 580 579 578 2 156 158 161 -3 -2.15 0.27Wellington (E) LT Wellington (SW) 33 582 580 584 1 219 220 242 -22 -10.09 1.46Wellington (E) RT Ruahine (N) 34 582 579 583 49 882 931 998 -67 -7.24 2.17Ruahine (N) LT Wellington (E) 35 576 578 597 27 955 982 1068 -86 -8.75 2.68Ruahine (N) RT Wellington (SW) 36 592 579 580 3 45 48 58 -10 -21.25 1.40Moxham (S) LT Goa (W) 37 565 563 504 4 4 18 -14 -347.50 4.20Moxham (S) TH Moxham (N) 38 565 563 540 3 117 120 121 -1 -0.92 0.10Moxham (S) RT Goa (E) 39 565 563 601z 6 6 5 1 18.33 0.47Goa (E) LT Moxham (S) 40 601z 563 565 1 1 1 0 -10.00 0.10Goa (E) TH Goa (W) 41 601z 563 504 5 5 0 5 100.00 3.16Goa (E) RT Moxham (N) 42 601z 563 540 7 7 8 -1 -12.86 0.33Moxham (N) LT Goa (E) 43 540 563 601z 2 2 3 -1 -35.00 0.46Moxham (N) TH Moxham (S) 44 540 563 565 1 114 115 79 36 30.96 3.61Moxham (N) RT Goa (W) 45 540 563 504 11 11 3 9 77.27 3.27Goa (W) LT Moxham (N) 46 504 563 540 30 30 39 -9 -29.00 1.48Goa (W) TH Goa (E) 47 504 563 601z 9 9 10 -1 -6.67 0.20Goa (W) RT Moxham (S) 48 504 563 565 12 12 0 12 98.33 4.78Moxham (S) LT Taurima (W) 49 683 511 512 44 44 57 -13 -30.23 1.87Moxham (S) TH Hataitai (N) 50 683 511 541 1 117 118 110 8 6.61 0.73Hataitai (N) TH Moxham (S) 51 541 511 683 1 97 98 62 37 37.24 4.09Hataitai (N) RT Taurima (W) 52 541 511 512 1 110 111 99 12 10.45 1.13Taurima (W) LT Hataitai (N) 53 512 511 541 131 131 109 22 16.95 2.03Taurima (W) RT Moxham (S) 54 512 511 683 1 39 40 23 17 43.00 3.07Ruahine (S) TH Mt Victoria Tunl (W) 55 88 515 182 53 905 958 982 -24 -2.51 0.77Taurima (E) LT Ruahine (S) 56 513 516 515 14 14 26 -12 -85.00 2.66Taurima (E) RT Mt Victoria Tunl (W) 57 513 514 182 1 134 135 132 4 2.59 0.30Mt Victoria Tunl (W) LT Taurima (W) 58 501 182 513 1 176 177 132 45 25.65 3.65Mt Victorial Tunl (W) TH Ruahine (S) 59 501 182 515 30 995 1025 1048 -23 -2.22 0.71Aldelaide (S) LT Rugby (W) 60 170 171 169 36 804 840 901 -61 -7.30 2.08Rugby (E) LT Adelaide (S) 61 168 665 666 16 498 514 524 -10 -1.87 0.42Rugby (E) TH Rugby (W) 62 167 168 169 43 1091 1134 1169 -35 -3.12 1.04Paterson (E) LT Dufferin (S) 63 166 159 165 54 1083 1137 1114 23 2.01 0.68Kent (N) LT Paterson (E) 64 157 164 158 31 1185 1216 1179 37 3.01 1.06Kent (N) TH Dufferin (S) 65 157 165 161 5 506 511 549 -38 -7.42 1.65Kent (N) LT Dufferin (S) 66 151 155 162 36 1691 1727 1704 23 1.34 0.56Buckle (W) LT Cambridge (N) 67 11 153 152 16 627 643 630 13 2.01 0.51Buckle (W) TH Dufferin (E) 68 11 154 155 0 6 6 27 -21 -343.33 5.10Dufferen (W) LT Hania St 69 162 163 659z 41 41 21.3 19.7 48.05 3.53Dufferen (W) TH Ellice St 70 162 163 89 79 79 68.4 10.6 13.42 1.23Hania St (N) TH Dufferin St 71 659z 163 249 46 46 25.8 20.2 43.91 3.37Ignore This Row 89 163 249 32.9Ellice St (E) LT Dufferin St 72 89 175 157 50 50 56.8 -6.8 -13.60 0.93Sussex (S) LT Buckle (W) 73 10 174z 342 71 1293 1364 1474 -110 -8.06 2.92Suxxex (S) RT Buckle (E) 74 216 10 11 8 633 641 647 -6 -0.86 0.22Rugby (E) TH Rugby (W) 75 169 172 174 38 38 3 35 93.16 7.86Rugby (W) LT Sussex (N) 76 7 174 173 31 31 37 -6 -19.03 1.01Cambridge (S) TH Cambridge (N) 77 655 104 103 16 658 674 716 -42 -6.25 1.60Cambridge (S) RT Pirie (E) 78 140 104 105 30 30 29 1 4.33 0.24Pirie (E) LT Kent (S) 79 105 104 143 52 52 40 12 23.85 1.83Pirie (E) RT Kent (N) 80 105 104 103 1 28 29 11 18 62.41 4.05Kent (N) LT Pirie (E) 81 141 104 105 1 40 41 13 28 69.27 5.49Kent (N) TH Kent (S) 82 141 104 143 13 725 738 770 -32 -4.31 1.16Vivian (W) LT Cambridge (N) 83 621z 104 103 2 89 91 81 10 10.88 1.07Vivian (W) TH Pirie (E) 84 621z 104 105 3 47 50 85 -35 -70.80 4.30Vivian (W) RT Kent (S) 85 621z 104 143 23 923 946 992 -46 -4.83 1.47Cambridge (S) LT Courtenay (W) 86 656 490 487 6 187 193 240 -47 -24.25 3.18Cambridge (S) TH Cambridge (N) 87 492 484 491 12 545 557 494 63 11.33 2.75Cambridge (S) RT Majoribanks (E) 88 492 484 489 46 46 69 -23 -48.91 2.97Majoribanks (E) LT Kent (S) 89 489 484 493 3 49 52 48 4 7.88 0.58Majoribanks (E) TH Courtenay (W) 90 489 484 490 43 43 54 -11 -26.05 1.61Majoribanks (E) RT Cambridge (N) 91 489 484 491 103 103 104 -1 -0.78 0.08Kent (N) LT Majoribanks (E) 92 494 484 489 3 84 87 87 0 0.11 0.01Kent (N) TH Kent (S) 93 494 484 493 8 551 559 576 -17 -3.09 0.73Kent (N) RT Courtenay (W) 94 494 484 490 4 71 75 67 8 10.80 0.96Courtenay (W) LT Cambridge (N) 95 490 491 368x 1 66 67 74 -7 -10.60 0.85Courtenay (W) TH Majoribanks (E) 96 490 484 489 1 60 61 78 -17 -27.05 1.98Courtenay (W) RT Kent (S) 97 490 484 493 1 163 164 133 31 18.66 2.51Tasman (S) LT Buckle (W) 98 186 8 368 36 36 8 28 78.06 6.00Tasman (S) TH Tory (N) 99 186 8 139z 45 45 33 12 27.56 1.99Buckle (E) LT Tasman (S) 100 342 8 186 4 4 4 0 0.00 0.00Buckle (E) TH Buckle (W) 101 342 8 368 67 1217 1284 1362 -78 -6.09 2.15Buckle (E) RT Tory (N) 102 342 8 139z 4 79 83 109 -26 -30.72 2.61Tory (N) TH Tasman (S) 103 139z 8 186 3 128 131 132 -1 -1.07 0.12Tory (N) RT Buckle (W) 104 139z 8 368 4 169 173 167 6 3.29 0.44Tory (S) TH Tory (N) 105 266 102 101 3 116 119 120 -1 -0.42 0.05Tory (S) RT Vivian (E) 106 266 102 621z 33 33 17 16 49.39 3.27Tory (N) LT Vivian (E) 107 101 102 621z 2 65 67 101 -34 -50.90 3.72Tory (N) TH Tory (S) 108 101 102 266 5 215 220 238 -18 -7.95 1.16Vivian (W) LT Tory (N) 109 341z 102 101 5 144 149 134 15 9.80 1.23Vivian (W) TH Vivian (E) 110 341z 102 621z 25 1013 1038 1037 1 0.10 0.03Vivian (W) RT Tory (S) 111 341z 102 266 3 101 104 94 10 9.81 1.03Tory (S) LT Courtenay (W) 112 500 271 496 49 49 58 -9 -18.57 1.24Tory (S) TH Tory (N) 113 500 271 497 6 187 193 178 15 7.67 1.09Tory (S) RT Courtenay (E) 114 500 271 270 2 24 26 79 -53 -202.31 7.27Courtenay (E) LT Tory (S) 115 270 271 500 7 50 57 83 -26 -45.61 3.11Courtenay (E) TH Courtenay (W) 116 270 271 496 3 234 237 240 -3 -1.14 0.17Courtenay (E) RT Tory (N) 117 270 271 497 17 17 44 -27 -158.82 4.89Tory (N) LT Courtenay (E) 118 497 271 270 12 12 5 7 56.67 2.32Tory (N) TH Tory (S) 119 497 271 500 196 196 210 -14 -6.89 0.95Tory (N) RT Courtenay (W) 120 497 271 496 27 27 22 6 20.37 1.12Courtenay (W) LT Tory (N) 121 496 271 497 5 17 22 11 11 49.55 2.68Courtenay (W) TH Courtenay (E) 122 496 271 270 1 262 263 244 19 7.38 1.22Courtenay (W) RT Tory (S) 123 496 271 500 34 34 37 -3 -9.12 0.52Taranaki (S) LT Arthur (W) 124 364y 9 629y 7 237 244 285 -41 -16.84 2.53Taranaki (S) TH Taranaki (N) 125 364y 9 674 9 298 307 301 6 2.08 0.37Buckle (E) LT Taranaki (S) 126 13 9 14 9 128 137 113 24 17.30 2.12Ignore This Row 13 9 364y 16Buckle (E) TH Arthur (W) 127 13 9 629y 45 1060 1105 987 118 10.64 3.64Buckle (E) RT Taranaki (N) 128 630y 9 674 13 223 236 202 34 14.49 2.31Taranaki (N) TH Taranaki (S) 129 360z 9 364y 23 518 541 511 30 5.49 1.29Ignore This Row 360z 9 14 447Taranaki (N) RT Arthur (W) 130 674 9 629y 10 124 134 90 44 32.54 4.12Taranaki (S) LT Abel Smith (W) 131 353 50 232 59 59 65 -6 -9.32 0.70Taranaki (S) TH Taranaki (N) 132 353 50 636 2 423 425 450 -25 -5.95 1.21

Turn Flow Comparison: 12:00-13:00 IP Period

2/11/2009 12:27 p.m.

NO. ANODE BNODE CNODE COUNT COUNT COUNT MODELLED DIFFER- % Diff GEHTaranaki (N) TH Taranaki (S) 133 636 50 353 16 603 619 597 22 3.57 0.90Taranaki (N) RT Abel Smith (W) 134 636 50 232 61 61 108 -47 -77.21 5.12Abel Smith (W) LT Taranaki (N) 135 232 50 636 104 104 58 46 44.23 5.11Taranaki (S) TH Taranaki (N) 136 132 117 620z 4 432 436 470 -34 -7.71 1.58Taranaki (S) RT Vivian (E) 137 123 117 134 2 115 117 95 22 18.55 2.11Taranaki (N) LT Vivian (E) 138 620z 117 134 4 294 298 212 86 28.72 5.36Taranaki (N) TH Taranaki (S) 139 620z 117 123 11 403 414 374 40 9.76 2.04Vivian (W) LT Taranaki (S) 140 358z 117 620z 3 99 102 94 8 7.84 0.81Vivian (W) TH Vivian (E) 141 358z 117 134 27 862 889 956 -67 -7.50 2.20Vivian (W) RT Taranaki (S) 142 653 117 123 6 253 259 294 -35 -13.36 2.08Taranaki (S) LT Ghuznee (W) 143 228 99 137 118 118 129 -11 -9.32 0.99Taranaki (S) TH Taranaki (N) 144 228 99 638 10 413 423 428 -5 -1.23 0.25Taranaki (N) TH Taranaki (S) 145 638 99 228 7 407 414 392 22 5.36 1.11Taranaki (N) RT Ghuznee (W) 146 638 99 137 74 74 90 -16 -21.76 1.78Ghuznee (W) LT Taranaki (N) 147 137 99 638 4 269 273 253 20 7.25 1.22Ghuznee (W) RT Taranaki (S) 148 137 99 228 4 288 292 189 103 35.24 6.63Taranaki (S) LT Dixon (W) 149 199 82z 325 3 86 89 96 -7 -7.64 0.71Taranaki (S) TH Taranaki (N) 150 199 82z 287 1 406 407 449 -42 -10.29 2.03Taranaki (S) RT Courtenay (E) 151 339z 82z 273 166 166 133 33 19.64 2.66Courtenay (E) LT Taranaki (S) 152 273 82z 339z 1 101 102 78 24 23.33 2.51Courtenay (E) TH Dixon (W) 153 273 82z 325 1 157 158 172 -14 -8.80 1.08Courtenay (E) RT Taranaki (N) 154 273 82z 287 1 42 43 30 13 29.53 2.10Taranaki (N) LT Courtenay (E) 155 287 82z 273 1 68 69 63 6 8.41 0.71Taranaki (N) TH Taranaki (S) 156 287 82z 339z 309 309 321 -12 -3.85 0.67Taranaki (N) RT Dixon (W) 157 287 82z 325 1 40 41 37 4 9.27 0.61Manner (W) LT Taranaki (N) 158 297 82z 287 45 45 45 0 -0.44 0.03Manner (W) TH Courtenay (E) 159 297 82z 273 5 79 84 125 -41 -48.93 4.02Manner (W) RT Taranaki (S) 160 297 82z 339z 1 71 72 72 0 0.42 0.04Cuba(S) LT Karo (W) 161 19 51 361 3 23 26 26 0 -1.15 0.06Cuba (S) TH Cuba (N) 162 19 51 49 1 48 49 69 -20 -40.41 2.58Karo (E) LT Cuba (S) 163 629y 51 19 18 18 31 -13 -69.44 2.54Karo (E) TH Karo (W) 164 629y 51 361 61 1345 1406 1285 121 8.58 3.29Karo (E) RT Cuba (N) 165 629y 51 49 1 58 59 49 10 17.63 1.42Cuba (N) TH Cuba (S) 166 49 51 19 2 67 69 34 35 50.43 4.84Cuba (N) RT Karo (W) 167 49 51 361 42 42 22 20 48.10 3.58Karo (SE) LT Victoria (S) 168 360 362 363 15 120 135 107 28 20.74 2.55Karo (SE) TH Karo (NW) 169 360 357y 366y 49 1341 1390 1231 159 11.46 4.40Ignore This Row 362 357y 357 994Victoria (N) TH Victoria (S) 170 29 358 357y 10 592 602 633 -31 -5.08 1.23Victoria (N) RT Karo (NW) 171 29 358 357 12 214 226 281 -55 -24.42 3.47Victoria (N) LT Vivian (E) 172 628 106 251 131 131 117 14 10.99 1.29Victoria (N) TH Victoria (S) 173 628 106 336 12 442 454 469 -15 -3.30 0.70Vivian (W) LT Victoria (N) 174 52z 115 139 26 26 31 -5 -19.23 0.94Vivian (W) TH Vivian (E) 175 115 106 251 32 1082 1114 1116 -2 -0.19 0.06Vivian (W) RT Victoria (S) 176 115 106 336 10 363 373 374 -1 -0.35 0.07Victoria (SW) LT Ghuznee (NW) 177 359z 94 652 11 11 9 2 18.18 0.63Victoria (SW) TH Victoria (NE) 178 359z 94 365 12 12 6 6 50.83 2.04Victoria (SW) RT Ghuznee (SE) 179 359z 94 96 8 8 28 -20 -255.00 4.78Ghuznee (SE) LT Victoria (SW) 180 364 94 359z 93 93 111 -18 -19.68 1.81Ghuznee (SE) TH Ghuznee (NW) 181 364 94 652 2 143 145 163 -18 -12.21 1.43Ghuznee (SE) RT Victoria (NE) 182 96 94 365 3 67 70 46 24 34.86 3.21Victoria (NE) LT Ghuznee (SE) 183 82 94 96 1 141 142 139 3 2.25 0.27Victoria (NE) TH Victoria (SW) 184 82 94 359z 7 292 299 314 -15 -5.05 0.86Victoria (NE) RT Ghuznee (NW) 185 365 94 652 28 28 18 10 34.29 1.99Ghuznee (NW) LT Victoria (NE) 186 652 94 365 89 89 63 26 29.10 2.97Ghuznee (NW) TH Ghuznee (SE) 187 652 94 96 404 404 412 -8 -1.91 0.38Ghuznee (NW) RT Victoria (SW) 188 652 94 359z 14 297 311 284 28 8.84 1.60Victoria (SW) LT Dixon (NW) 189 200 279 79 3 71 74 79 -5 -6.08 0.52Victoria (SW) TH Victoria (NE) 190 200 279 366w 4 43 47 37 10 21.70 1.58Dixon (SE) LT Victoria (SW) 191 81 279 200 4 77 81 62 19 23.58 2.26Dixon (SE) TH Dixon (NW) 192 81 279 79 2 163 165 178 -13 -7.82 0.99Dixon (SE) RT Victoria (NE) 193 81 279 366w 5 42 47 64 -17 -35.11 2.22Victoria (NE) TH Victoria (SW) 194 294 279 200 5 417 422 407 15 3.60 0.75Victoria (NE) RT Dixon (NW) 195 366w 279 79 2 64 66 67 -1 -0.76 0.06Manners (S) TH Manner (N) 196 343y 308 364x 9 78 87 123 -36 -41.38 3.51Victoria (N) TH Victoria (S) 197 309 342z 312 5 480 485 489 -4 -0.87 0.19Victoria (S) RT Manners (N) 198 309 342z 308 2 163 165 159 6 3.82 0.50Willis (SW) LT Abel Smith (NW) 199 38 43 206 27 27 25 2 6.67 0.35Willis (SW) TH Wellington Urban Mway 200 38 43 356 27 255 282 266 16 5.53 0.94Willis (SW) TH Willis (NE) 201 38 43 337 30 313 343 322 21 6.21 1.17Karo (SE) LT Abel Smith (NW) 202 367 43 206 74 74 81 -7 -9.59 0.81Karo (SE) TH Wellington Urban Mway 203 367 43 356 56 1173 1229 1125 104 8.45 3.03Karo (SE) RT Willis (NE) 204 357 43 337 5 308 313 308 5 1.69 0.30Abel Smith (NW) LT Wellington Urban Mway 205 206 43 356 5 5 5 0 6.00 0.14Abel Smith (NW) TH Willis (NE) 206 206 43 337 14 14 11 3 22.14 0.88Willis (S) TH Willis (N) 207 178 28 36 30 267 297 314 -17 -5.72 0.97Webb (E) LT Willis (S) 208 267z 28 178 22 354 376 372 4 1.01 0.20Webb (E) RT Willis (N) 209 27 28 36 5 331 336 340 -4 -1.07 0.20Willis (S) LT Aro (W) 210 28 36 39 2 220 222 234 -12 -5.54 0.81Willis (S) TH Willis (N) 211 28 36 41 32 378 410 419 -9 -2.15 0.43Aro (W) LT Willis (N) 212 39 41 38 2 214 216 228 -12 -5.42 0.79Willis (S) TH Willis (N) 213 260 52z 357z 11 372 383 368 15 3.92 0.77Willis (S) RT Vivian (E) 214 260 52z 115 9 263 272 260.7 11.3 4.15 0.69Vivan (W) LT Willis (N) 215 356z 357z 256 7 54 61 53.8 7.2 11.80 0.95Vivian (W) TH Vivian (E) 216 356z 52z 115 33 1208 1241 1260 -19 -1.53 0.54Willis (SW) LT Ghuzness (NW) 217 73 67 68 4 123 127 120.4 6.6 5.20 0.59Willis (SW) TH Willis (NE) 218 73 67 303 12 210 222 237.1 -15.1 -6.80 1.00Willis (SW) RT Ghuzness (NE) 219 73 67 652 3 92 95 30 65 68.42 8.22Ghuznee (NE) TH Ghuznee (NW) 220 652 67 68 135 135 153.4 -18.4 -13.63 1.53Ghuznee (NE) RT Willis (NE) 221 652 67 303 2 31 33 38.9 -5.9 -17.88 0.98Willis (NE) LT Ghuznee (SE) 222 303 67 652 200 200 202.6 -2.6 -1.30 0.18Willis (NE) RT Ghuznee (NW) 223 303 67 68 1 8 9 10.7 -1.7 -18.89 0.54Ghuznee (NW) LT Willis (NE) 224 68 67 303 34 34 0 34 100.00 8.25Ghuznee (NW) TH Ghuzness (SE) 225 68 67 652 11 505 516 526.2 -10.2 -1.98 0.45Willis (SW) LT Dixon (NW) 226 317 79 296z 10 10 8.3 1.7 17.00 0.56Willis (SW) TH Willis (NE) 227 317 79 319 15 276 291 268.5 22.5 7.73 1.35Dixon (SE) LT Willis (SW) 228 279 79 317 2 37 39 40.2 -1.2 -3.08 0.19Dixon (SE) TH Dixon (NW) 229 279 79 296z 1 95 96 100.3 -4.3 -4.48 0.43Dixon (SE) RT Willis (NE) 230 279 79 319 8 146 154 184 -30 -19.48 2.31Willis (NE) TH Willis (SW) 231 319 79 317 3 146 149 151.7 -2.7 -1.81 0.22Willis (NE) RT Dixon (NW) 232 319 79 296z 5 5 5.7 -0.7 -14.00 0.30Dixon (NW) LT Willis (NE) 233 296z 79 319 32 32 33.3 -1.3 -4.06 0.23Dixon (NW) RT Willis (SW) 234 296z 79 317 25 25 24 1 4.00 0.20Willis (SW) LT Manners (NW) 235 297z 301 315 2 159 161 178.7 -17.7 -10.99 1.36Willis (SW) TH Willis (NE) 236 297z 301 313 20 295 315 320.2 -5.2 -1.65 0.29Manners (SE) LT Willis (SW) 237 343z 301 297z 1 1 2.4 -1.4 -140.00 1.07Manners (SE) TH Manners (NW) 238 343z 301 315 5 116 121 111.9 9.1 7.52 0.84Manners (SE) RT Willis (NE) 239 343z 301 313 3 123 126 166.9 -40.9 -32.46 3.38Manners (NW) LT Willis (NE) 240 315 301 313 5 143 148 148.2 -0.2 -0.14 0.02Manners (NW) RT Willis (SW) 241 315 301 297z 2 139 141 143.4 -2.4 -1.70 0.20



241 0%Total

GEH SummaryGEH <5

GEH <10GEH >12

2/11/2009 12:27 p.m.


Evan Bay Pde (S) LT Wellington (W) 1 608 610 603 2 109 111 114 -3 -2.34 0.25Evan Bay Pde (S) TH Evan Bay Pde (N) 2 608 604 609 2 142 144 145 -1 -0.56 0.07Evan Bay Pde (S) RT Cobham (E) 3 608 604 614 1 62 63 64 -1 -1.75 0.14Cobham (E) LT Evan Bay Pde (S) 4 605 608 616 43 43 45 -2 -4.88 0.32Cobham (E) TH Wellington (W) 5 605 604 610 19 1166 1185 1194 -9 -0.73 0.25Cobham (E) RT Evan Bay Pde (N) 6 676 604 609 3 208 211 210 1 0.43 0.06Evan Bay Pde (N) LT Cobham (E) 7 609 614 606 431 431 434 -3 -0.67 0.14Evan Bay Pde (N) TH Evan Bay Pde (S) 8 609 604 608 2 197 199 201 -2 -0.95 0.13Evan Bay Pde (N) RT Wellington (W) 9 609 604 610 90 90 92 -2 -1.78 0.17Wellington (W) LT Evan Bay Pde (N) 10 621 609 617 49 49 50 -1 -1.63 0.11Wellington (W) TH Cobham (E) 11 621 604 614 10 1128 1138 1076 62 5.47 1.87Wellington (W) RT Evan Bay Pde (S) 12 610 604 608 95 95 89 6 6.53 0.65Kilbimia (S) LT Wellington (W) 13 600 667 581 73 73 91 -18 -24.38 1.97Kilbimia (S) TH Hanmilton (N) 14 600 585 586 153 153 142 11 6.99 0.88Kiilbinia (S) RT Wellington (E) 15 600 585 602 43 43 44 -1 -1.86 0.12Wellington (E) LT Kilbimie (S) 16 611 600 590 215 215 218 -3 -1.21 0.18Wellington (E) TH Wellington (W) 17 611 585 667 21 1161 1182 1120 63 5.29 1.84Wellington (E) RT Hanmilton (N) 18 602 585 586 25 25 77 -52 -208.80 7.30Hanmilton (N) LT Wellington (E) 19 586 585 602 1 101 102 98 4 4.31 0.44Halminton (N) TH Kilbimie (S) 20 586 585 600 1 107 108 130 -22 -20.74 2.05Hanmilton (N) RT Wellingotn (W) 21 586 585 667 18 18 6 12 67.78 3.54Wellington (W) LT Hanmilton (N) 22 601 585 586 24 24 19 5 19.58 1.01Wellington (W) TH Wellington (E) 23 601 585 602 9 1120 1129 1069 60 5.33 1.82Wellington (W) RT Kilbimie (S) 24 667 585 600 104 104 70 34 32.50 3.62Wellington (E) TH Wellington (W) 25 599 596 597 21 1186 1207 1159 48 4.01 1.41Wellington (E) RT Moxham (N) 26 599 596 598 66 66 62 4 5.76 0.47Moxham (N) LT Wellington (E) 27 598 599 581 9 9 10 -1 -10.00 0.29Moxham (N) RT Wellington (W) 28 598 596 597 6 6 16 -10 -166.67 3.02Wellington (W) LT Moxham (N) 29 578 597 598 12 12 24 -12 -96.67 2.75Wellinigton (W) TH Wellington (W) 30 597 596 599 9 1239 1248 1145 103 8.25 2.98Wellington (SW) LT Ruahine (N) 31 580 583 576 1 176 177 138 39 22.03 3.11Welliington (SW) RT Wellington (E) 32 580 579 578 131 131 149 -18 -13.44 1.49Wellington (E) LT Wellington (SW) 33 582 580 584 2 218 220 226 -6 -2.77 0.41Wellington (E) RT Ruahine (N) 34 582 579 583 19 968 987 949 38 3.86 1.22Ruahine (N) LT Wellington (E) 35 576 578 597 9 1117 1126 1019 107 9.47 3.25Ruahine (N) RT Wellington (SW) 36 592 579 580 126 126 112 14 11.35 1.31Moxham (S) LT Goa (W) 37 565 563 504 15 15 40 -25 -165.33 4.74Moxham (S) TH Moxham (N) 38 565 563 540 189 189 264 -75 -39.47 4.96Moxham (S) RT Goa (E) 39 565 563 601z 1 1 1 0 10.00 0.10Goa (E) LT Moxham (S) 40 601z 563 565 1 1 1 1 50.00 0.58Goa (E) TH Goa (W) 41 601z 563 504 3 3 0 3 100.00 2.45Goa (E) RT Moxham (N) 42 601z 563 540 2 2 4 -2 -75.00 0.90Moxham (N) LT Goa (E) 43 540 563 601z 5 5 8 -3 -62.00 1.21Moxham (N) TH Moxham (S) 44 540 563 565 180 180 193 -13 -6.94 0.92Moxham (N) RT Goa (W) 45 540 563 504 15 15 0 15 100.00 5.48Goa (W) LT Moxham (N) 46 504 563 540 59 59 6 53 89.66 9.27Goa (W) TH Goa (E) 47 504 563 601z 18 18 16 2 9.44 0.41Goa (W) RT Moxham (S) 48 504 563 565 11 11 0 11 100.00 4.69Moxham (S) LT Taurima (W) 49 683 511 512 50 50 75 -25 -50.20 3.17Moxham (S) TH Hataitai (N) 50 683 511 541 178 178 200 -22 -12.08 1.56Hataitai (N) TH Moxham (S) 51 541 511 683 1 147 148 173 -25 -16.69 1.95Hataitai (N) RT Taurima (W) 52 541 511 512 111 111 101 11 9.46 1.02Taurima (W) LT Hataitai (N) 53 512 511 541 1 181 182 191 -9 -5.11 0.68Taurima (W) RT Moxham (S) 54 512 511 683 67 67 28 39 57.76 5.61Ruahine (S) TH Mt Victoria Tunl (W) 55 88 515 182 20 1121 1141 996 145 12.72 4.44Taurima (E) LT Ruahine (S) 56 513 516 515 26 26 20 6 22.31 1.21Taurima (E) RT Mt Victoria Tunl (W) 57 513 514 182 135 135 156 -21 -15.70 1.76Mt Victoria Tunl (W) LT Taurima (W) 58 501 182 513 2 247 249 220 29 11.81 1.92Mt Victorial Tunl (W) TH Ruahine (S) 59 501 182 515 9 1230 1239 1083 156 12.62 4.59Aldelaide (S) LT Rugby (W) 60 170 171 169 10 865 875 985 -110 -12.58 3.61Rugby (E) LT Adelaide (S) 61 168 665 666 11 632 643 659 -16 -2.53 0.64Rugby (E) TH Rugby (W) 62 167 168 169 9 1329 1338 1336 3 0.19 0.07Paterson (E) LT Dufferin (S) 63 166 159 165 20 1247 1267 1162 105 8.26 3.00Kent (N) LT Paterson (E) 64 157 164 158 11 1485 1496 1301 195 13.04 5.22Kent (N) TH Dufferin (S) 65 157 165 161 0 714 714 821 -107 -14.92 3.84Kent (N) LT Dufferin (S) 66 151 155 162 11 2037 2048 1901 147 7.19 3.31Buckle (W) LT Cambridge (N) 67 11 153 152 5 868 873 835 38 4.39 1.31Buckle (W) TH Dufferin (E) 68 11 154 155 62 62 113 -51 -81.45 5.41Dufferen (W) LT Hania St 69 162 163 659z 22 22 24 -2 -10.00 0.46Dufferen (W) TH Ellice St 70 162 163 89 58 58 56 2 2.93 0.22Hania St (N) TH Dufferin St 71 659z 163 249 98 98 68 30 30.51 3.28

89 163 249 98Ellice St (E) LT Dufferin St 72 89 175 157 144 144 119 25 17.15 2.15Sussex (S) LT Buckle (W) 73 10 174z 342 25 1230 1255 1484 -229 -18.26 6.19Suxxex (S) RT Buckle (E) 74 216 10 11 6 803 809 905 -96 -11.84 3.27Rugby (E) TH Rugby (W) 75 169 172 174 65 65 4 61 93.23 10.29Rugby (W) LT Sussex (N) 76 7 174 173 30 30 58 -28 -93.33 4.22Cambridge (S) TH Cambridge (N) 77 655 104 103 3 809 812 856 -44 -5.36 1.51Cambridge (S) RT Pirie (E) 78 140 104 105 2 67 69 75 -6 -8.26 0.67Pirie (E) LT Kent (S) 79 105 104 143 79 79 38 41 51.77 5.35Pirie (E) RT Kent (N) 80 105 104 103 64 64 65 -1 -1.72 0.14Kent (N) LT Pirie (E) 81 141 104 105 63 63 11 52 83.17 8.64Kent (N) TH Kent (S) 82 141 104 143 5 1006 1011 1106 -95 -9.44 2.93Vivian (W) LT Cambridge (N) 83 621z 104 103 1 72 73 45 28 38.77 3.69Vivian (W) TH Pirie (E) 84 621z 104 105 74 74 99 -25 -33.24 2.65Vivian (W) RT Kent (S) 85 621z 104 143 6 955 961 841 121 12.54 4.01Cambridge (S) LT Courtenay (W) 86 656 490 487 161 161 198 -37 -23.23 2.79Cambridge (S) TH Cambridge (N) 87 492 484 491 4 728 732 589 143 19.48 5.55Cambridge (S) RT Majoribanks (E) 88 492 484 489 80 80 78 2 2.38 0.21Majoribanks (E) LT Kent (S) 89 489 484 493 47 47 42 5 11.49 0.81Majoribanks (E) TH Courtenay (W) 90 489 484 490 50 50 56 -6 -11.80 0.81Majoribanks (E) RT Cambridge (N) 91 489 484 491 201 201 203 -2 -0.75 0.11Kent (N) LT Majoribanks (E) 92 494 484 489 2 247 249 249 0 0.04 0.01Kent (N) TH Kent (S) 93 494 484 493 5 902 907 914 -7 -0.78 0.24Kent (N) RT Courtenay (W) 94 494 484 490 58 58 42 16 28.28 2.32Courtenay (W) LT Cambridge (N) 95 490 491 368x 38 38 44 -6 -14.47 0.86Courtenay (W) TH Majoribanks (E) 96 490 484 489 80 80 100 -20 -24.88 2.10Courtenay (W) RT Kent (S) 97 490 484 493 192 192 282 -90 -46.82 5.84Tasman (S) LT Buckle (W) 98 186 8 368 182 182 130 53 28.85 4.21Tasman (S) TH Tory (N) 99 186 8 139z 70 70 67 3 4.00 0.34Buckle (E) LT Tasman (S) 100 342 8 186 1 1 2 -1 -100.00 0.82Buckle (E) TH Buckle (W) 101 342 8 368 25 1137 1162 1398 -236 -20.34 6.60Buckle (E) RT Tory (N) 102 342 8 139z 59 59 78 -19 -32.71 2.33Tory (N) TH Tasman (S) 103 139z 8 186 247 247 251 -4 -1.54 0.24Tory (N) RT Buckle (W) 104 139z 8 368 253 253 200 53 21.07 3.54Tory (S) TH Tory (N) 105 266 102 101 96 96 110 -14 -14.58 1.38Tory (S) RT Vivian (E) 106 266 102 621z 62 62 62 0 0.65 0.05Tory (N) LT Vivian (E) 107 101 102 621z 51 51 50 1 2.55 0.18Tory (N) TH Tory (S) 108 101 102 266 401 401 354 47 11.72 2.42Vivian (W) LT Tory (N) 109 341z 102 101 94 94 110 -16 -17.34 1.61Vivian (W) TH Vivian (E) 110 341z 102 621z 7 991 998 868 130 13.01 4.25Vivian (W) RT Tory (S) 111 341z 102 266 109 109 103 6 5.87 0.62Tory (S) LT Courtenay (W) 112 500 271 496 1 90 91 93 -2 -1.76 0.17Tory (S) TH Tory (N) 113 500 271 497 82 82 69 13 15.37 1.45Tory (S) RT Courtenay (E) 114 500 271 270 18 18 34 -16 -91.11 3.20Courtenay (E) LT Tory (S) 115 270 271 500 50 50 58 -8 -15.20 1.04Courtenay (E) TH Courtenay (W) 116 270 271 496 194 194 259 -65 -33.25 4.29Courtenay (E) RT Tory (N) 117 270 271 497 25 25 30 -5 -19.20 0.92Tory (N) LT Courtenay (E) 118 497 271 270 30 30 29 1 4.33 0.24Tory (N) TH Tory (S) 119 497 271 500 339 339 321 18 5.43 1.01Tory (N) RT Courtenay (W) 120 497 271 496 21 21 22 -1 -2.38 0.11Courtenay (W) LT Tory (N) 121 496 271 497 1 46 47 50 -3 -5.96 0.40Courtenay (W) TH Courtenay (E) 122 496 271 270 323 323 368 -45 -13.81 2.40Courtenay (W) RT Tory (S) 123 496 271 500 1 63 64 39 25 39.69 3.55Taranaki (S) LT Arthur (W) 124 364y 9 629y 5 238 243 208 35 14.57 2.36Taranaki (S) TH Taranaki (N) 125 364y 9 674 1 280 281 357 -76 -27.01 4.25Buckle (E) LT Taranaki (S) 126 13 9 14 2 163 165 181 -16 -9.88 1.24Ignore This Row 13 9 364y 58Buckle (E) TH Arthur (W) 127 13 9 629y 21 1240 1261 1307 -46 -3.62 1.28Buckle (E) RT Taranaki (N) 128 630y 9 674 2 181 183 177 6 3.39 0.46Taranaki (N) TH Taranaki (S) 129 360z 9 364y 5 740 745 740 5 0.62 0.17Ignore This Row 360z 9 14 698Taranaki (N) RT Arthur (W) 130 674 9 629y 2 188 190 98 92 48.42 7.67Taranaki (S) LT Abel Smith (W) 131 353 50 232 43 43 96 -53 -123.95 6.39Taranaki (S) TH Taranaki (N) 132 353 50 636 3 387 390 421 -31 -7.87 1.52

Turn Flow Comparison: 17:00-18:00 PM Period

2/11/2009 12:26 p.m.

NO. ANODE BNODE CNODE COUNT COUNT COUNT MODELLED DIFFER- % Diff GEHTaranaki (N) TH Taranaki (S) 133 636 50 353 7 655 662 794 -132 -19.95 4.90Taranaki (N) RT Abel Smith (W) 134 636 50 232 98 98 126 -28 -28.27 2.62Abel Smith (W) LT Taranaki (N) 135 232 50 636 109 109 52 58 52.75 6.42Taranaki (S) TH Taranaki (N) 136 132 117 620z 2 423 425 473 -48 -11.32 2.27Taranaki (S) RT Vivian (E) 137 123 117 134 1 83 84 62 22 25.83 2.54Taranaki (N) LT Vivian (E) 138 620z 117 134 502 502 338 164 32.61 7.99Taranaki (N) TH Taranaki (S) 139 620z 117 123 4 546 550 646 -96 -17.36 3.91Vivian (W) LT Taranaki (S) 140 358z 117 620z 4 58 62 53 9 14.52 1.19Vivian (W) TH Vivian (E) 141 358z 117 134 6 585 591 678 -87 -14.64 3.43Vivian (W) RT Taranaki (S) 142 653 117 123 3 242 245 280 -35 -14.12 2.14Taranaki (S) LT Ghuznee (W) 143 228 99 137 121 121 136 -15 -12.73 1.36Taranaki (S) TH Taranaki (N) 144 228 99 638 6 389 395 375 20 5.06 1.02Taranaki (N) TH Taranaki (S) 145 638 99 228 2 616 618 708 -90 -14.58 3.50Taranaki (N) RT Ghuznee (W) 146 638 99 137 106 106 107 -1 -0.57 0.06Ghuznee (W) LT Taranaki (N) 147 137 99 638 5 313 318 311 7 2.23 0.40Ghuznee (W) RT Taranaki (S) 148 137 99 228 2 425 427 301 126 29.46 6.59Taranaki (S) LT Dixon (W) 149 199 82z 325 3 105 108 123 -15 -13.80 1.39Taranaki (S) TH Taranaki (N) 150 199 82z 287 4 445 449 437 12 2.67 0.57Taranaki (S) RT Courtenay (E) 151 339z 82z 273 4 172 176 173 3 1.93 0.26Courtenay (E) LT Taranaki (S) 152 273 82z 339z 87 87 141 -54 -62.53 5.09Courtenay (E) TH Dixon (W) 153 273 82z 325 2 139 141 196 -55 -38.72 4.21Courtenay (E) RT Taranaki (N) 154 273 82z 287 31 31 35 -4 -12.58 0.68Taranaki (N) LT Courtenay (E) 155 287 82z 273 149 149 144 5 3.49 0.43Taranaki (N) TH Taranaki (S) 156 287 82z 339z 2 541 543 575 -32 -5.87 1.35Taranaki (N) RT Dixon (W) 157 287 82z 325 52 52 21 31 59.04 5.07Manner (W) LT Taranaki (N) 158 297 82z 287 30 30 34 -4 -13.33 0.71Manner (W) TH Courtenay (E) 159 297 82z 273 111 111 156 -45 -40.63 3.90Manner (W) RT Taranaki (S) 160 297 82z 339z 92 92 135 -43 -46.20 3.99Cuba(S) LT Karo (W) 161 19 51 361 2 146 148 48 100 67.30 10.05Cuba (S) TH Cuba (N) 162 19 51 49 74 74 92 -18 -24.59 2.00Karo (E) LT Cuba (S) 163 629y 51 19 20 20 22 -2 -8.50 0.37Karo (E) TH Karo (W) 164 629y 51 361 28 1625 1653 1570 83 5.02 2.07Karo (E) RT Cuba (N) 165 629y 51 49 36 36 12 24 67.22 4.95Cuba (N) TH Cuba (S) 166 49 51 19 120 120 109 12 9.58 1.08Cuba (N) RT Karo (W) 167 49 51 361 95 95 24 71 74.42 9.15Karo (SE) LT Victoria (S) 168 360 362 363 1 177 178 101 77 43.43 6.55Karo (SE) TH Karo (NW) 169 360 357y 366y 29 1707 1736 1543 193 11.13 4.77Ignore This Row 362 357y 357 1485Victoria (N) TH Victoria (S) 170 29 358 357y 7 1321 1328 1191 137 10.32 3.86Victoria (N) RT Karo (NW) 171 29 358 357 1 401 402 522 -120 -29.93 5.60Victoria (N) LT Vivian (E) 172 628 106 251 1 55 56 48 8 14.64 1.14Victoria (N) TH Victoria (S) 173 628 106 336 1113 1113 982 131 11.79 4.05Vivian (W) LT Victoria (N) 174 52z 115 139 44 44 49 -5 -10.23 0.66Vivian (W) TH Vivian (E) 175 115 106 251 12 794 806 702 104 12.90 3.79Vivian (W) RT Victoria (S) 176 115 106 336 569 569 444 125 21.93 5.54Victoria (SW) LT Ghuznee (NW) 177 359z 94 652 11 11 5 6 53.64 2.08Victoria (SW) TH Victoria (NE) 178 359z 94 365 20 20 27 -7 -32.50 1.35Victoria (SW) RT Ghuznee (SE) 179 359z 94 96 13 13 33 -20 -152.31 4.14Ghuznee (SE) LT Victoria (SW) 180 364 94 359z 137 137 114 23 16.93 2.07Ghuznee (SE) TH Ghuznee (NW) 181 364 94 652 214 214 247 -33 -15.51 2.19Ghuznee (SE) RT Victoria (NE) 182 96 94 365 40 40 45 -5 -11.75 0.72Victoria (NE) LT Ghuznee (SE) 183 82 94 96 1 124 125 161 -36 -28.88 3.02Victoria (NE) TH Victoria (SW) 184 82 94 359z 1 600 601 606 -5 -0.80 0.20Victoria (NE) RT Ghuznee (NW) 185 365 94 652 54 54 33 22 39.81 3.27Ghuznee (NW) LT Victoria (NE) 186 652 94 365 32 32 26 6 18.13 1.08Ghuznee (NW) TH Ghuznee (SE) 187 652 94 96 1 564 565 633 -68 -12.09 2.79Ghuznee (NW) RT Victoria (SW) 188 652 94 359z 434 434 338 96 22.17 4.90Victoria (SW) LT Dixon (NW) 189 200 279 79 93 93 81 12 12.47 1.24Victoria (SW) TH Victoria (NE) 190 200 279 366w 27 27 28 -1 -3.70 0.19Dixon (SE) LT Victoria (SW) 191 81 279 200 2 133 135 69 66 48.89 6.53Dixon (SE) TH Dixon (NW) 192 81 279 79 2 220 222 200 22 10.05 1.54Dixon (SE) RT Victoria (NE) 193 81 279 366w 1 38 39 100 -61 -155.64 7.29Victoria (NE) TH Victoria (SW) 194 294 279 200 647 647 677 -30 -4.68 1.18Victoria (NE) RT Dixon (NW) 195 366w 279 79 153 153 154 -1 -0.72 0.09Manners (S) TH Manner (N) 196 343y 308 364x 1 64 65 157 -92 -141.23 8.72Victoria (N) TH Victoria (S) 197 309 342z 312 801 801 871 -70 -8.74 2.42Victoria (S) RT Manners (N) 198 309 342z 308 221 221 228 -7 -2.99 0.44Willis (SW) LT Abel Smith (NW) 199 38 43 206 30 30 37 -7 -23.33 1.21Willis (SW) TH Wellington Urban Mway 200 38 43 356 5 278 283 322 -39 -13.85 2.25Willis (SW) TH Willis (NE) 201 38 43 337 6 401 407 394 13 3.22 0.65Karo (SE) LT Abel Smith (NW) 202 367 43 206 79 79 80 -1 -0.76 0.07Karo (SE) TH Wellington Urban Mway 203 367 43 356 29 1898 1927 1891 36 1.87 0.83Karo (SE) RT Willis (NE) 204 357 43 337 1 131 132 100 32 24.24 2.97Abel Smith (NW) LT Wellington Urban Mway 205 206 43 356 14 14 22 -8 -57.14 1.89Abel Smith (NW) TH Willis (NE) 206 206 43 337 57 57 98 -41 -71.40 4.63Willis (S) TH Willis (N) 207 178 28 36 12 449 461 462 -1 -0.11 0.02Webb (E) LT Willis (S) 208 267z 28 178 775 775 789 -14 -1.79 0.50Webb (E) RT Willis (N) 209 27 28 36 1 483 484 546 -62 -12.75 2.72Willis (S) LT Aro (W) 210 28 36 39 450 450 458 -8 -1.67 0.35Willis (S) TH Willis (N) 211 28 36 41 12 482 494 549 -55 -11.19 2.42Aro (W) LT Willis (N) 212 39 41 38 215 215 220 -5 -2.47 0.36Willis (S) TH Willis (N) 213 260 52z 357z 5 335 340 361 -21 -6.26 1.14Willis (S) RT Vivian (E) 214 260 52z 115 2 211 213 235 -22 -10.14 1.44Vivan (W) LT Willis (N) 215 356z 357z 256 69 69 82 -13 -19.42 1.54Vivian (W) TH Vivian (E) 216 356z 52z 115 10 1203 1213 953 260 21.44 7.90Willis (SW) LT Ghuzness (NW) 217 73 67 68 100 100 81 19 19.30 2.03Willis (SW) TH Willis (NE) 218 73 67 303 5 246 251 275 -24 -9.68 1.50Willis (SW) RT Ghuzness (NE) 219 73 67 652 118 118 84 34 28.47 3.34Ghuznee (NE) TH Ghuznee (NW) 220 652 67 68 273 273 271 2 0.77 0.13Ghuznee (NE) RT Willis (NE) 221 652 67 303 20 20 16 4 20.50 0.97Willis (NE) LT Ghuznee (SE) 222 303 67 652 1 248 249 241 8 3.05 0.49Willis (NE) RT Ghuznee (NW) 223 303 67 68 29 29 50 -21 -73.79 3.40Ghuznee (NW) LT Willis (NE) 224 68 67 303 55 55 46 9 16.73 1.30Ghuznee (NW) TH Ghuzness (SE) 225 68 67 652 601 601 669 -68 -11.23 2.68Willis (SW) LT Dixon (NW) 226 317 79 296z 20 20 17 3 16.00 0.75Willis (SW) TH Willis (NE) 227 317 79 319 5 377 382 350 32 8.35 1.67Dixon (SE) LT Willis (SW) 228 279 79 317 30 30 44 -14 -47.33 2.33Dixon (SE) TH Dixon (NW) 229 279 79 296z 134 134 188 -54 -40.30 4.26Dixon (SE) RT Willis (NE) 230 279 79 319 2 174 176 205 -29 -16.36 2.09Willis (NE) TH Willis (SW) 231 319 79 317 1 186 187 186 1 0.75 0.10Willis (NE) RT Dixon (NW) 232 319 79 296z 6 6 7 -1 -18.33 0.43Dixon (NW) LT Willis (NE) 233 296z 79 319 80 80 87 -7 -8.50 0.74Dixon (NW) RT Willis (SW) 234 296z 79 317 61 61 59 2 3.11 0.25Willis (SW) LT Manners (NW) 235 297z 301 315 310 310 309 1 0.26 0.05Willis (SW) TH Willis (NE) 236 297z 301 313 7 349 356 361 -5 -1.52 0.29Manners (SE) LT Willis (SW) 237 343z 301 297z 1 1 1 0 -30.00 0.28Manners (SE) TH Manners (NW) 238 343z 301 315 1 183 184 190 -6 -3.21 0.43Manners (SE) RT Willis (NE) 239 343z 301 313 115 115 199 -84 -73.30 6.72Manners (NW) LT Willis (NE) 240 315 301 313 172 172 204 -32 -18.31 2.30Manners (NW) RT Willis (SW) 241 315 301 297z 1 191 192 147 45 23.49 3.46



241 0%GEH >12

Total

GEH SummaryGEH <5

GEH <10

2/11/2009 12:26 p.m.


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APPENDIX�B�

Journey�Times�–�Distance/Time�Graphs�


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APPENDIX�C�

Data�Collection�Maps�

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APPENDIX�D�

Signal�Times�


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AM�Peak�

Observed ModelledCy cle Length (s) 81 81

A Phase 51 46

D Phase 33 39 E Phase 15 15

Int 480 - Willis/ GhuzneePeak Hour Averages

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Observed ModelledCy cle Length (s) 118 106 A Phase 63 71 B Phase 37 29

Int 530 - Vivian/ VictoriaPeak Hour Averages

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Observed ModelledCy cle Length (s) 104 120 A Phase 32 29 B Phase 13 11 D Phase 17 18 E Phase 34 31 G Phase 15 18

Int 450 - Taranaki/ Courtney/ DixonPeak Hour Averages

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Observed ModelledCy cle Length (s) 120 110 A Phase 25 22 E Phase 13 13 C Phase 24 24 D Phase 19 22 B Phase 18 18

Int 470 - Kent/ Cambridge/ Courtney/ MajoribanksPeak Hour Averages

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Observed ModelledCy cle Length (s) 118 106 A Phase 44 44 B Phase 14 14 C Phase 26 26 D Phase 16 16

Int 475 - Elizabeth/ Kent/ CambridgePeak Hour Averages

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Int 400 - Boulcott/ Willis/ MannersPeak Hour Averages

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Observed ModelledCy cle Length (s) 95 80 A Phase 34 40 D Phase 26 25 E Phase 40 35

Int 1300 - Wellington/ Kilbirnie/ HamiltonPeak Hour Averages

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Int 430 - Victoria/ DixonPeak Hour Averages

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Int 510 - Ghuznee/ TaranakiPeak Hour Averages

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Int 570 - Vivian/ Kent/ PiriePeak Hour Averages

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Int 550 - Vivian/ TaranakiPeak Hour Averages

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Int 645 - Patterson/ DufferinPeak Hour Averages

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Observed ModelledCy cle Length (s) 95 80 A Phase 35 34 C Phase 19 19 D Phase 24 24 E Phase 24 23

Int 1310 - Wellington/ Cobham/ Evans BayPeak Hour Averages

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Observed ModelledCy cle Length (s) 111 103 A Phase 52 49 B Phase 14 15 C Phase 34 36

Int 620 - Buckle/ Taranaki/ ArthurPeak Hour Averages

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Int 680 - Wallace/ BidwellPeak Hour Averages

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Int 425 - Dixon/ WillisPeak Hour Averages

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Int 605 - Karo/ Mowon/ Willis/ Abel SmithPeak Hour Averages

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Int 610 - Karo/ VictoriaPeak Hour Averages

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Int 650 - Rugby/ AdelaidePeak Hour Averages

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Int 490 - Ghuznee/ VictoriaPeak Hour Averages


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Inter�Peak�


A Phase 52 46



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PM�Peak�


A Phase 34 47



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APPENDIX�E�

Peer�Review�Report�

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Wellington CBD S-Paramics ModelIssue No. 2 S-Paramics Audit

Prepared forNZ Transport Agency Level 9, PSIS House 20 Ballance Street PO Box 5084, Lambton Quay Wellington

Report ref: Job No 42773-001 30th June

Aurecon New Zealand Limited Page 2

Quality Assurance

Audit Reference: Job No 42773-001 as part of contract Title: Wellington CBD S-Paramics Model

Auditor Model: Andrew Mein Auditor SCATS: Lachlan Beban Report Prepared By: Andrew Mein Report Reviewed By: Lachlan Beban

Issue Date Revision Description 1 18th June 2009 First issue 2 30th June 2009 Final Issue

Aurecon New Zealand Limited Page 3

Contents

1. Audit overview 41.1 Purpose 41.2 Overview 41.3 Conduct of the audit 51.4 Audit report convention 51.5 Definitions 6

2. Audit 72.1 Standards 72.2 Submitted model networks 72.3 Submitted reports 72.4 Submitted support material 7

3. Audit schedule 83.1 The project 83.2 The audit 83.3 Model scope 8

4. Summary of Audit Recommendations 94.1 The model 94.2 The brief 94.3 Purpose of use 9

5. Summary of audit recommendations 115.1 The brief 115.2 Model form 115.3 Site visit 125.4 Standard files 125.5 General network construction 195.6 Model operation 215.7 Model outputs 225.8 Model stability 225.9 Model calibration 235.10 Model validation 265.11 Fit for use 26

Wellington CBD Model Printed copies of this document are uncontrolled Job No 42773-001 Issue No. 1 11/06/2009 Page 4

1. Audit overview 1.1 Purpose This report summarises the findings of a technical audit undertaken on traffic models developed using the S-PARAMICS suite of traffic micro-simulation software covering the area of the Wellington CBD.

The purpose of the audit is to:

� Confirm the quality of the data and the appropriateness of its use within the model � Ensure that the modelling results are sufficiently accurate and robust for the decisions which it is

intended to inform � Help the learning processes of both the Contractor (in using the model), and the Project Manager (in

preparing briefs and interpreting model results)

It would not be practical for the audit to examine every component of the modelling work, and it cannot therefore certify that the modelling is “correct” in every respect.

1.2 Overview The audit examines the following aspects of the work if made available to the audit team:

� The Brief. This is the basis of the modelling work. The audit examines the adequacy of the brief, and conformity of the work to the brief.

� The network model. The audit checks the sources of geometric data, and carries out spot checks to confirm correct scale and check the layouts of one or more critical elements of the network. It also checks special coding of link categories, speeds, lane functions (turning movements permitted, and “stacking” where appropriate), lane restrictions (e.g. bus lanes or transit lanes) and look-ahead (“signposts”) for suitability.

� Traffic signal control. Where the network model includes traffic signals, the audit checks the source of traffic signal control data (phases, cycles and offsets), and spot checks critical intersections for accuracy.

� Travel demand data. The audit checks the sources of travel demand data, and that the estimation of base year and future year modelled demand is acceptable.

� Vehicle data. The audit checks whether standard default vehicle data is used, the need for any non-standard vehicle data, and the source and suitability of non-standard data.

� Driver behavioural data. The audit checks whether standard default behavioural data is used, the need for any non-standard data, and the source and suitability of non-standard data.

� Public Transport routes. The audit checks the sources and modelling of public transport routes, stops and service frequencies.

� Traffic assignment. Where the modelled network provides alternative routes for any trips, the audit checks the assignment process used, including the cost function, assignment algorithm, driver familiarity, perturbations, strategic routes (if defined), and any route restrictions for special vehicle types.

� Model calibration. The audit checks the process used for calibrating the model, the data against which it is calibrated, the changes made to the model to improve the calibration, and the final accuracy of calibration achieved.

� Model validation. The audit examines whether the model has been validated against data independent of that used for calibration, and the results of the validation.

� Model application. The audit checks the results obtained from the model for reasonability, and (where suitable sensitivity tests have been carried out) for robustness.

� Documentation of model development and application. The audit checks that all the above aspects of the modelling work are adequately documented.


1.3 Conduct of the audit The Audit Team shall:

� Examine and assess all of the items listed in the audit schedule. � Ensure that the Lead Auditor is kept informed of the progress of the audit, and any matters of concern

that are identified.

Where the audit schedule uses the term calibration, it refers to the process of estimating model parameters by fitting model results to a set of observations. The term validation refers to a subsequent process of checking model outputs against a second set of observations, independent of the set used for calibration. The modeller may subsequently undertake a process of adjustment to improve the fit between model outputs and the second set of observations. No further validation is possible unless a third set of observations can be found, which are independent of the sets used for calibration and validation.

Where standard “default” values are available for model parameters, and the audit finds that other values have been adopted, care should be taken to determine the reasons for that choice, the source of the non-standard values, and their reasonableness having regard to values used for other modelling projects, or values obtained from direct observation.

Where spot checks are called for, the audit team shall select a small number of critical points in the model for detailed checking. In addition, base and future models should be subjected to a visual check of the operating model, to confirm that traffic movements, and queues appear reasonable.

Where the audit schedule calls for an assessment of the reasonableness of model results, consideration should be given to theoretical and logical expectations, and to any modelled or observed outcomes of similar projects.

In examining sensitivity tests as an indication of the robustness of the model results, consideration should be given to the risk that the model results might lead to an incorrect decision, in terms of:

� The risk that a given modelling assumption might be incorrect � The sensitivity of the modelling results to likely error in the assumption � The sensitivity of the final decision to the likely variation in model results � Throughout the audit, consideration should be given to the Brief for the modelling work, in terms of

whether the brief adequately specified the work, and whether the work complies with the brief

The over-riding consideration in conducting the audit should be “fitness for purpose”. The audit team must therefore keep clearly in mind the intended use of the model, and the decisions, which its results will inform. The model results, and even the observed data used to calibrate the model, are not precise values. They represent a range of probable values, which can be expressed as a probable error or a confidence interval. What is important is that:

� the degree of accuracy is adequate for the decisions to be made � decision makers are aware of the accuracy of the information they are given

1.4 Audit report convention Throughout the report, paragraph formatting has been used to assist in reading the audit.

There are four levels of formatting provided to indicate suggested model changes, which are colour coded as follows to indicate their level of priority.

Low: This style of paragraph is a suggested “good practice” tip and is not critical to the model operation or results

Medium: This style of paragraph suggests a desirable alteration that may improve the model operation or results, it is however not essential.


High: This style of paragraph is a strong recommendation to correct or amend the discussed element or provide further justification for changing or coding the element.

Critical: This style of paragraph identifies an element that is critical to the model that effects model operation and the results and requires alteration.

1.5 Definitions Calibration Refers to the process of estimating model parameters by fitting model

results to a set of observations Validation A subsequent process of checking model outputs against a second set of

observations, independent of the set used for calibration S-Paramics The microscopic traffic simulation suite of software developed by SIAS

Limited.


2. Audit 2.1 Standards Standards DMRB / NZTA Economic Evaluation Manual Brief A model scope was provided Reporting None

2.2 Submitted model networks Enter Model Name d Base Adaptive AM SR 45; d Base Adaptive IP SR 45; d Base Adaptive

PM SR 45

2.3 Submitted reports Document Reference Calibration documentation provided Wellington CBD Paramics Modelling Validation Report

2.4 Submitted support material The audit will refer to the group of documents below as “model support material” and will be referenced individually as per below.

Workbook Reference Additional calibration documentation provided PeakHourTurnCountComparison_WCIB.xls


3. Audit schedule 3.1 The project Location / Route / Area Wellington CBD Project Description Development of S-Paramics model of Wellington CBD Purpose of Modelling Assess future land use and network improvements within the Wellington

CBDModel developed by Opus International Consultants

3.2 The audit Auditor - Andrew Mein Dates 11/06/2009

3.3 Model scope Geographical extent Agreed with the auditor at the outset of the model Years modelled 2009 Time periods modelled Morning Peak (07:00 – 10:00), Inter-peak (11:00 – 14:00), Evening Peak

(17:00 – 18:00)


4. Summary of Audit Recommendations 4.1 The model Item Section Ref. Recommendations

Priority Critical: Priority High: Demands 5.4.9 The models presented are peak hour models only and should be

clearly stated in the calibration report as such. Signal Timing Review 5.9 Anomalies with phase splits should be highlighted in the

reportingPriority Medium: Categories 5.4.6 It is good practice to use categories for specific corridors.

Queue Definition 5.4.7 The queue definition should be included in the reporting Mean Target Headway 5.4.7 Attention should be drawn to the non-default setting and justification

of.Modifiers 5.4.14 Better use of wide end and wide starts though the model. Urban/ Highway 5.4.14 Wellington Upper Highway should be coded as highway to ensure

consistency with NZ lane utilisation. Nextlanes 5.4.17 Widespread use of next lanes is not recommended, consideration

should be given to reducing the number of these within the model(s). Right turn bays and left turn slip lanes

5.5.3 When coding networks in NZ check on-street left turn and blocking of through traffic and model appropriately.

Version 5.4.27 The version of S-Paramics used should be included in the calibration report

Model Differences Peak Hour Models

5.5.1 Differences in the standard files between peak hour models should be highlighted in the reporting.

SCATS Calibration 5.9 Left turn from the Boulcott North approach at Intersection 400 Boulcott/ Willis/ Manners had been allocated to signal group (sg) 4 and should be sg1

Priority Low: New Zealand Left Turn 5.4.7 Highlight in the reporting that the setting is enabled with FUSE.

Periods 5.4.19 A description within the period file is recommended.

4.2 The brief

Item Section Ref Recommendations Model Scope Letter A model scoping letter was provided which stated the

modelling methodology

4.3 Purpose of use Are the simulation models suitable for the purpose for which they were constructed? - Assessment of alternatives around the

The models presented follow industry standards with network coding and demand methodology deemed suitable for the purposes of testing the proposed engineering solutions within


Basin Reserve the Basin Reserve. There are a number of issues that require addressing regarding the calibration in particular relating to the signal timings for the three peak periods and the replication of the cycle lengths. Suggested changes to nodes 294, 125 and 377 should be implemented. With these issues addressed, it is considered that the models as presented meet the industry recognised standards and are suitable to be taken forward to future testing of the proposed options.


5. Summary of audit recommendations The following section expands on the audit summary with examples where appropriate.

5.1 The brief No modelling brief was provided for this audit, therefore no comment is made on the how the brief has been addressed. A model scoping letter was received which detailed the methodology adopted to derive survey data as input to the model.

5.2 Model form

5.2.1 Introduction Many of the comments within this audit are intended not only to highlight issues relevant to the modelling of the Wellington CBD, but are also intended to guide the modeller in aspects of good practice where these apply to using the S-Paramics microscopic simulation package.

5.2.2 Geometric data The AM, Inter-peak and PM models represent the area referred to as the Wellington CBD. The extent of the model study area is shown in Figure 1.

Figure 1 : Wellington CBD


The study area as shown superimposed on a 1 kilometre grid. It can be seen that the modelled area is approximately 3 km long by 3 km wide.

Visual inspection of the road widths and vehicle dimensions supported by checks on the input data files, indicate that the model is constructed at the scale 1:1 which ensures correct vehicle operation, reaction to the road geometry and other vehicles.

5.3 Site visit Given the location, a site visit was not undertaken by the reviewer. This review is merely looking at the model form and methodologies employed to assess the model against good practice.

5.4 Standard files

5.4.1 Introduction The standard files are the S-Paramics model input files. The following is a list of the audited files.

5.4.2 Annotation A good model description was used in the presented models, however should include the Peak naming.

5.4.3 Behaviour The default values have been retained.

5.4.4 Buses

Bus Routes and Schedules Bus Routes and schedule information was obtained from ArcGIS data provided by Greater Wellington Regional Council (GWRC). These have been appropriately coded in the presented models.

Bus stops Bus stop locations are clearly marked with a clearly defined boarding and alighting methodology applied.

5.4.5 Car parks Car parks have not been applied with this model.

5.4.6 Categories The categories file contains speeds, major / minor, costs factors, colours of the road (for auditing and checking), overtaking parameters, the numbers of lanes and lastly the speed. The only other parameter that tends not to be used in the category file is urban or highway. Because of the definition of highway based on UK driving rules, it is strongly recommended that ‘highway type’ is not used for coding normal links. It may be used on a zone connector to improve the loading operation of cars onto the network, but only there.

10 categories have been coded. Grouped in lanes of 1 to 4, the speeds range from 30 kph to 80 kph. The application of categories to the model is not ideal. The majority of links through the model are defined as category 1 to 4. It is recommended that a different link category is applied for a particular corridor. This can make things easier when undertaking wholesale changes to a corridor.

These categories in the presented models are reasonable for the modelled road network.

It is good practice to use categories for specific corridors.


5.4.7 Configuration

Release style The release style of precise has been used.

Model start time and simulation time The morning peak period model start time is 08:00:00 and the model with duration of 3 hours.

The inter-peak period model start time is 11:00:00 and the model with duration of 3 hours.

The evening peak period model start time is 16:00:00 and the model with duration of 3 hours.

Time step The recommended value of time steps is 2 and is used in this model.

Cost coefficients Cost coefficients are discussed in Section 5.7

Queue definition Opus have used a non-default queue definition as recommended by the auditor. This queue criterion is Aurecons standard criteria and is not a standard adopted by the industry as a whole. This is not to say the queue criteria as stated above is to be adopted as a standard for S-Paramics it is merely addressing the standard queue definition as defined by S-Paramics as being inconsistent with observed values.

The reporting should include mention of these non default settings.

The queue definition used is as follows:

� General: Vehicle queued when: Speed 7 kph, gap 5 m, both toggled; Vehicle no longer queued when: Speed 7.5 kph, gap 6 m, either toggled

� Other settings: min length 2, recurse 8, toggle off ‘include signalised links in non signal queues’ � Multiple queues: Joining all the queues together toggled.

The queue definition should be included in the reporting.

Mean target headway

The Mean Headway parameter influences vehicle behaviour as they follow other vehicles through the network. The headway of each vehicle will be affected by a variety of elements including the link speed and type, the vehicle's top speed, aggression, size, the dynamics of the vehicle type, etc.

In S-Paramics the headway is the time in seconds between the tail of the vehicle leading, and the front of the vehicle following. Note, in a Transport Engineering context headway is commonly measured from the front of the first vehicle to the front of next vehicle. If making on-site headway measurements for the purpose of calibration ensure that the headway is timed from the rear of the leading vehicle to the front of the following vehicle. This will enable a direct comparison with the model settings without having to account for vehicle lengths.

The headways, influenced by the inputs noted above, are then given a skewed distribution according the aggression and link type. This skewed distribution will be +-50% on urban roads and between +100 and -50% on highways.


The default value is 1.0 second however here at Aurecon we would recommend mean target headway of 0.8. This is based on research undertaken with this parameter and reflects conditions in particular areas.

A value of 1.5 is utilised in the presented models. This is higher than the default and with this, further clarification has been provided by Opus regarding the use of the parameter. The clarification provided assesses on street loop data and clarifies the headways of observed vehicles in the area are in the order of 1.5 seconds. It is therefore considered appropriate, in this instance to use a setting of 1.5 seconds. However, any modeller using the model should be aware of this setting and the influence this has.

Attention should be drawn to the non-default setting and justification of.

Mean reaction time The mean reaction time of each driver, in seconds, is associated with the lag in time between a change in speed of the preceding vehicle and the following vehicles reaction to the change. The default value is 1.0 second and is utilised in this model.

Network minimum gap The network minimum gap parameter sets the gap between each vehicle when a queue forms. Extensive research undertaken by Aurecon has revealed that the default setting (for versions 2005.1 and earlier) of two metres within the model actually represents almost a four metre gap when applied. For this reason, a value of 0.8 is typically used in models run in 2005.1 and earlier. It was also found that with versions 2006.1 and above a value of 1.6 should be used to reflect a two meter gap.

A value of 1.6 is utilised in the presented models which is run in version 2008.1

New Zealand left turn The New Zealand left turn argument is not enabled in the presented models. This may occur from the use of baseplusFUSE, as this can be changed within baseplusFUSE but would not be saved to the file. It is recommended that within the calibration report is stated that the NZLeftTurn rule is enabled in FUSE.

Highlight in the reporting the setting is enabled with FUSE.

Signal Settings When run with baseplusFUSE software the differences between the settings become obsolete.

5.4.8 Controllers The controllers file is where the SNMP port number is set. The port should be set to 2100.

In the presented models the SNMP port is set to 2100.

5.4.9 Demands A review of the demand matrix methodology shows that the process is appropriate.

A cordoned one hour trip demand matrix extracted from the Wellington City SATURN model was used as the prior with S-Paramics ME. This is standard practice to use a higher tier model to attain the origin destination data. With a combination of survey data, and constraints, ME was used to better reflect observed count data. Comparison of before and after the ME process demonstrates that the ME process did not adversely skew demands and is considered appropriate.

Following this, the demand matrices have been split to account for various restrictions applied to the model around the Basin and Victoria Street. This is seen as appropriate and kept to a minimum.

The derived demand matrix was complied for the peak hour for each respective period. The shoulders of the peak demand totals were derived from observed traffic count data for each period. The proportion of each shoulder peak compared to the Peak hour was calculated and applied to derive the shoulder peak matrices.


It would have been considered more appropriate to derive the shoulders of the peak demand matrices using the corresponding traffic count data and ME process to better reflect each area within the model rather than applying a global factor. Without this, it is considered that the shoulders of the peak are merely warm-up and cool down periods and should be used with extreme caution with regards presenting information pertaining to these periods. This is further emphasized with the calibration statistics presented which are produced merely for the peak hour and not shoulders nor full model period.

The models presented are seen to be peak hour models only and should be clearly stated in the calibration report as such.

5.4.10 Detectors The detectors should be 5.0 m in length and the positioning of the stoplines should be such back from the stop line to ensure appropriate detection of vehicles. The detectors in the models presented appear to be further back from the stopline than may be desired; however observations of the SCATS operation show this to be operating without issue.

5.4.11 Hazards Only default hazard lengths were used in the presented models. The non-standard hazard lengths that where coded in the presented models are tabled below:

Node Location Comment 7 Intersection of Rugby

St/ Tasman St Reduced to 0, unclear why changed, however this is single lane from all approaches and surrounding intersections are single lane, therefore this does not cause adverse effects.

10/ 216 Sussex St/ Buckle St Hazard reduced to 150m/ 50m respectively, this causes some vehicles to get in lane late when exiting from Sussex St heading to Buckle St/ Cambridge Tce.

11 Buckle St/ Cambridge Tce.

Reduced to 150m, unclear reasoning for this however does not affect the model operation.

41 Aro St/ Willis St Reduced to 50m, unclear reasoning for this however does not affect the model operation.

52z Willis St/ Vivian St Increased to 300m, unclear reasoning for this however this does not affect the model operation. It is noted that increasing this length has minimal affect given the number of hazards in the vicinity of this intersection.

168 Adelaide Rd/ Rugby St Reduced to 50m, unclear reasoning for this however this does not affect the model operation.

172/ 173 Rugby St/ Sussex St Reduced to 50m, unclear reasoning for this however this does not affect the model operation.

178 Willis Street Reduced to 30m, there is no hazard at this point so unsure why changed from default.

264 Willis Street Reduced to 15m, used to increase lane utilisation and is appropriately used.

Table 1 : Non Default Hazard Lengths

As per the comments in the table above, the above deviations from the default hazard lengths were appropriate in the context of the presented models.

It is good practice to review the hazards and assess their relevance.


5.4.12 Junctions A review of the junction turns and priorities showed up no likely coding errors. This was assessed comparing with Google Street map and reflects the layouts as presented.

5.4.13 Kerbs It is good practice to try to avoid widescale moving of kerbs and stoplines. The more kerbs and stoplines that are moved the longer it will take to load and run the model. The models show that only 16% of kerbs have been adjusted. It is noted that differences are apparent between model peaks relating to kerbs. These are considered minor but should be addressed.. See Section 5.5.1.

Because the stopline position is relative to the kerb, and the kerb position is relative to the node, it is important that these objects are moved in the order of nodes; kerbs; and then stoplines.

The presented models convey good positioning of kerbs.

5.4.14 Links

Link Class Based on the auditor’s review of the presented modelled networks to the Google maps street view, it appears appropriate link class has been coded to replicate on the ground conditions based on the way the model has been constructed. It is noted that the aerials are of a low quality and a site visit was not possible as part of this audit.

It is also noted that changes to the roading network have been implemented recently which may not be fully represented with Google maps.

One minor issue was noted regarding number of lanes on link 141:140, (southbound), it is considered that this should be coded as four lanes with lane one being bus only/ left turn. It is also noted that parked vehicles use this lane in off-peak times and that this may have been excluded from the model for this reason.

Link 141:140 should be four lanes, with lane one being coded as a bus lane.

Flags

Based on the auditor’s review of the presented modelled networks to the aerials provided, it appears appropriate flags have been coded to replicate on the ground conditions.

ModifiersBased on the auditor’s review of the presented modelled networks to the aerials provided, it appears appropriate link modifiers have been coded to replicate on the ground. Better use of wide end and wide starts are recommended but not considered critical. Wide end and wide starts have the effect of smoothing vehicle tracks when lane gain or lane drops occur on the network.

Better use of wide end and wide starts though the model.

Urban/Highway There are two very important aspects about driver behaviour in Paramics related to modification or classification of a link in an urban or highway situation, they are:

� default signposting is different � there is a propensity to stay to the left on a highway link

In the presented model(s) only the urban coding has been applied which is appropriate in the central CBD. Wellington Upper Highway Motorway to the north of Vivian Street has been coded as Highway. As stated above, coding a road such as this as highway not only changes the hazard lengths but more importantly forces vehicles to use stick to the left lane unless overtaking. Whilst in this case this is not an issue, it is


worth noting this for any future modelling undertaken and the implications this may have on the operation of the road.

It is recommended that links loading traffic on to the network on main routes should be coded as highway links to improve the loading operation of vehicles on to the network. This has been implemented within the model by the modeller assessing each zone loading in isolation.

Wellington Upper Highway should be coded as highway to ensure consistency with NZ lane utilisation.

Cost Factors Application of cost factors seem reasonable and are justified in the report.

5.4.15 Matrix Demand profiles appear to have been assigned to the demand matrices appropriately.

5.4.16 Measurements Measurements and calibration data sets are discussed in Section 5.9.

5.4.17 Nextlanes The use of nextlanes in the presented model(s) have been used excessively throughout the model. Using next lanes should be applied in moderation within a model. Next lanes should only be used as a last resort to ensure the correct lane is selected. The use of next lanes can hide the true cause of vehicles changing lane in the first place and can cause issues further up the link. Future users of the model should be aware of the next lanes applied to the models and take these into consideration with any alterations made.

Widespread use of next lanes is not recommended, consideration should be given to reducing the number of these within the model(s).

5.4.18 Nodes

PositioningIn general, the positioning of nodes appears to be appropriate. Nodes have been used where required for geometry, changes in road layout and for appropriate layout at a zone connector.

5.4.19 Periods The periodic files are related to the times of the day that require modelling. The periods files contains the period number, name and start time.

The table below shows the periods used with the morning peak period models.

1 07:00:00 Warm-up period 2 08:00:00 Peak hour period 3 09:00:00 Cool down period 4 10:00:00 Remainder Table 2 : Presented Models Periodic Setup Morning Peak

1 16:00:00 Warm-up period 2 17:00:00 Peak hour period 3 18:00:00 Cool down period


4 19:00:00 Remainder Table 3 : Presented Models Periodic Setup Evening Peak

The above times appear appropriate. It is recommended that a description is applied to each period within the periods file to verify each use.

A description within the period file is recommended.

5.4.20 Priorities

Priority Controlled Intersections A review of the priorities showed no issues in this regard.

Signal Controlled Intersections The signals in the presented models have phase and cycle times set by SCATS using the software b+ FUSE. A quick check of intersections within the model reveals the coding of the signals, with FUSE, to be appropriate.

5.4.21 Profiles A review of the profiles used within the presented model(s) reveal no issues. It is generally good practice to smooth the profiles from 15 minute data to 5 minute data. This is generally done to better reflect the smooth increase in traffic over time. Sudden increases from one 15 minute period to the next may be unrealistic and may influence the results greatly.

It has been noted in the calibration report that a check was undertaken to ensure to transfer between the periods was smooth in that there were not unrealistic spikes in demand being released.

Regarding internal profiles applied, it is noted that the CBD area was split into 4 blocks via a grid using Taranaki Street and Vivian Street separating the blocks. The southern section of the model was split in two blocks. The approaches used to generate profile data were intersection approaches heading out of the profile area with averages taken of traffic flow exiting the area in each time period. Land use area was considered to ensure selection of each area reflected similar land use.

The derivation of the internal profiles is appropriate.

5.4.22 Restrictions The use of restrictions within the presented model(s) is minimal and appears appropriate. The restrictions are clearly highlighted in the validation reporting.

5.4.23 Roundabouts There are no roundabouts in the presented model(s).

5.4.24 Stoplines Stopline positioning appears appropriate with the presented model(s).

5.4.25 Units The recommended mode for New Zealand is metric which has been used in the model.

5.4.26 Vehicles The vehicles files show that in total 10 vehicle types were applied. General traffic shows a split of 90% car, with the remainder LGV these are associated with Matrix 1. Four vehicle types are solely applicable to fixed


routes, e.g. bus routes. Matrix 2 refers to Heavy goods vehicles with a further two vehicles types assigned. Matrix 3 refers to trips heading the SH1 northbound and is assigned a car vehicle type only with matrix four assigned a separate vehicle type again car only.

Matrix 2 vehicles, heavy vehicles are shown to have familiarity set at 10% with perturbation set at 5%. It would be expected that HGV’s would tend to sick to main routes and not deviate from these, e.g. HGV;’s do not tend to rat run to avoid congestion. The settings of 10% familiarity are not considered significant given the low volumes; however these vehicle settings should be highlighted in the calibration reporting and the implications of future use if significant HGV growth is predicted.

Matrices 3/ 4 have been defined for cars only, this is traffic heading to SH1 and Adelaide Road are all assigned as car. HGV’s are minimal and have not been split in this regard. This is deemed acceptable but any future users of the model should be aware of this.

5.4.27 Version The version of the software last used to save the presented model(s) for audit is 2008.1 and is viewed in the same version.

The version is appropriate for the presented model(s). The version of the software used should be noted in the calibration report.

The version of S-Paramics used should be included in the calibration report

5.4.28 Waypoints No waypoints were used in the presented model(s).

5.4.29 Zones

Connectors The zone loading into the network can be critical, particularly on a link that is a representation of a busy road entering the study area that in reality has a high speed vehicle entry.

If defaults are retained then vehicles will load randomly along the length of the link and at an initial speed of zero.

To overcome this, the zone loading must be treated with the first node being a zone connector.

Secondly the link should be coded as a highway link to control the speed and loading position of the vehicles.

In the models presented the nodes have been changed to zone connector however these links, as mentioned previously, have not been altered to highway however the modeller has assessed each entry to the model on an individual basis in this regard.

5.5 General network construction

5.5.1 Model Differences Peak hour models

A check was carried out to assess differences between the various models presented; these are differences in the key files as noted above to ensure consistency not only between each model but also between the periods defined. A number of expected differences have been noted, namely relating to profile, demands and buspassenger loadings etc. A number of additional differences were noted between peak models. These relate to the following:


� Busroute links � Bus routes

Whilst the difference may be minor, there should be no differences between peak models unless specifically stated in the reporting. It has been noted by Opus that the model differences relating to bus route and bus route links are appropriate. This should be clearly defined in the reporting to ensure other modellers using the model are aware of the differences between periods.

Differences in the standard files between peak hour models should be highlighted in the reporting.

Periods

A check of the model differences between each period within each peak period model revealed no differences between these.

5.5.2 Node, Kerb and Stopline Positioning It is good practice to try and avoid wide scale moving of kerbs and stoplines. The more kerbs and stoplines that are moved, the longer it will take to load and run the model. Aligning kerbs to actual kerbs does not improve the simulation however, if the vehicle movements appear incorrect then kerbs and stoplines can be moved. The right way to do this is with good positioning of nodes and use of link characteristics etc.

Because the stopline position is relative to the kerb, and the kerb position is relative to the node it is important that these objects are moved in order:

� nodes; � kerbs; and then � stoplines

The presented model(s) exhibited good node, kerb, and stopline positioning.

5.5.3 Right turning bays and left turn slip lanes Generally, right turn bays and left turn slip lanes were coded appropriately in the presented models. It is noted that in some areas, with the New Zealand left turn rule enabled in the model that there could be an issue with left turning vehicles blocking through movements at certain locations. These are generally on the periphery of the network but future users of the model should be aware of this.

When coding networks in NZ check on-street left turn and blocking of through traffic and model appropriately.

5.5.4 Detectors The coded detectors have been coded correctly however there appears to be some issue relating to the position of advance and queue detectors at certain locations that require to be assessed to ensure these are as on street. The following table lists these detectors that were highlighted with Opus confirming the position of these with on street observations.

Detector Name Intersection Loop Comments 490_10 96:94 length 490 10 queue loop check location 490_11 96:94 length 490 11 queue loop check location 520_8 356z:52z length 520 8 queue loop check location 520_9 356z:52z length 520 9 queue loop check location 530_8 628:106 length 530 8 queue loop check location 530_9 628:106 length 530 9 queue loop check location


Detector Name Intersection Loop Comments 530_10 628:106 length 530 10 queue loop check location 530_11 115:106 length 530 11 queue loop check location 530_12 115:106 length 530 12 queue loop check location 550_10 358z:117 length 550 10 queue loop check location 550_11 358z:117 length 550 11 queue loop check location 630_6 139z:8 length 630 6 queue loop check location 650_3 168:665 length 650 3 check stopline/ loop location 650_4 168:665 length 650 4 check stopline/ loop location

1300_12 602:611 length 1300 12 advance loop not far enough back? - check location

1300_13 602:611 length 1300 13 advance loop not far enough back? - check location

1300_14 581:601 length 1300 14 advance not far enough back? - check location

1310_11 675:605 length 1310 11 advance loop check location 1310_12 675:605 length 1310 12 advance loop check location

1310_13 602:603 length 1310 13 advance loop too far back? - check location

1310_14 602:603 length 1310 14 advance loop too far back? - check location

Table 4 : Presented Models Detector Position Comments

5.5.5 Using Restrictions The use of restrictions within the presented model(s) is appropriate.

5.6 Model operation

5.6.1 Traffic Signal Control Traffic signal control is replicated in the model with the addition of SCATS to the model using FUSE. The application of SCATS, this is the mapping of the model turns to SCATS through FUSE has been carried out appropriately.

5.6.2 Traffic Assignment The generalised travel cost utilised by Paramics consists of the following three elements:

Cost = aT + bD + cP, where

T = travel time for trip/ travel time for link

D = distance of trip/length of link

P = monetary cost of trip or link

The default weightings (they must add up to 1.0) are a=1, b=0, c=0 i.e. the cost is solely reliant on travel time of the trip with no weighting from the distance or the toll.

In this model a = 0.6 and b = 0.4, so the perceived cost of the trip is weighed 60% on time and 40% on distance. This is within the range commonly used for urban areas. The assessment of what weightings should be used should be based on data or local knowledge relating to observed route choice in the area. The model is set to assign vehicles on an all or nothing basis which, given the size of the model appears to be appropriate.


5.6.3 Lane use behaviour In general the model lane behaviour is appropriate. There are some issues in certain areas where vehicles change lane rapidly due to hazard distances, or rather the number of hazards in the model however it is not considered critical. Users of the model should be aware of the location of the restrictions within the model and the lane changing that occurs at these points. It is considered that these are located in areas where they will have minimal impact on the operation.

5.6.4 Congestion Points Main areas of congestion are well documented in the reporting correspond with model run observations. As previously stated the auditor is assessing the model against industry standard practice as a site visit was not undertaken for the purposes of this audit.

It is noted that excessive off-the-network queuing occurs with Wellington Upper Highway in both the morning and evening peak periods. Off network queues were observed to be in the order of 200 to 350 vehicles. It should be noted in the reporting that this occurs and is reasonable.

5.7 Model outputs

5.7.1 Seed The random seeds used as a key factor in the generation of variant model runs and to assist in testing model stability were at value 0.

5.7.2 Runs It is strongly recommended that a minimum of 5, preferably 10 runs are undertaken with various seeds to ensure that the model is robust under slight variations of vehicle composition and release. The used seed value is reported in the ‘information’ file so that the run and results can be re-produced with the same model form and data set. 10 model runs have been used to assess the network and produce the various statistics reported and is considered acceptable for the size of model.

5.7.3 Measurements and validation of model outputs Calibration/ validation criteria for the Wellington CBD model is based solely upon the criteria as derived with the UK based DMRB. It is noted, in the calibration reporting, that the current NZ Economic Evaluation Manual is designed with a more strategic model in mind. Whilst this is true, it is still the current criteria in NZ that should be used when assessing a model within NZ.

The models developed by Aurecon are evaluated against not only the EEM criteria but other criteria such as those adopted in the USA etc. to show not only that the model meets the current NZ standards but also meets more appropriate standards for simulation modelling used elsewhere.

In order to confirm the model outputs are as reported, the presented model outputs were compared using in-house methodologies and confirms the model outputs compare well to those reported.

5.8 Model stability Model stability was not reported on in the Calibration Report. Tests of model stability were therefore undertaken by the auditor. The results are presented below and are for the initial modelling. The comparison of the outputs of ten model runs showed that the AM, IP and PM models are sufficiently stable.


Mean Delay Total Distance (m) Total Number Vehicles Mean Speed (kph) MEAN 263 67569479 43275 21 STD DEV 4 51700 18 0 MIN 255 67464568 43244 21 MAX 268 67670192 43300 22 RANGE 13 205624 56 1 CoV 1.37% 0.08% 0.04% 1.36%

Table 4 : Morning Peak Model Stability


Table 5 : Evening Peak Model Stability


Table 6 : Inter-Peak Model Stability

It is noted that further reporting of the model stability statistics has been presented for each period by Opus. These show the model to be stable with the exception of off network queuing which is shown to be highly variable between model runs.

5.9 Model calibration The Modeller used the following recorded data to calibrate the model:

� Turn Counts � Link Counts � Screenline Counts � Journey Times � Queue Lengths � SCATS Signal Count Data

Comparisons of the above observed data and the equivalent modelled data were presented in the Calibration Report. This was undertaken for the peak hours only for each respective period. Whilst this is in line with the criteria as stipulated in the EEM etc. it is considered appropriate to provided comparisons for the for the shoulders of the peak, in this case the first hour and last hour in addition to providing comparison for the full model period. The reason for this lies with the future scenarios being tested and perhaps to a lesser


extent the possible use of the model in testing different land-uses which peak periods may not correspond with the peak of the model as it stands. With congestion levels as observed currently, future growth in traffic demands may result in the spreading of the peak period demands to the shoulders. For this reason it is important to demonstrate the models are representing well these periods. This has not been undertaken, although it is noted that journey time comparisons have been presented for the pre-peak periods.

It is unfortunate the data sets for the full model period were not assessed as it is felt that this limits the model’s use in assessing some future scenarios. However if clearly stated that the model is a peak hour model then it is considered acceptable in this instance.

Turn Count/ Link Count Calibration

Comparisons show a good correlation between all of the above data meeting all relevant criteria. The criteria used assessed the GEH statistic, R-Squared, RMSE and turn count percentage differences in addition to turn count plots. Turn count data is presented in the reporting with additional link count data provided separately at the request of the auditor. Both data set comparisons show good correlation and meet the requirements as stipulated in the DMRB for the peak hour period.

Screenline Calibration

Three screenlines are reported with the calibration to ensure traffic entering and exiting the model by direction is within appropriate limits. The screenline locations appear appropriate however an additional screenline was requested to be reported by the auditor, this was a screenline on the external of the model area.

In general the screenline data demonstrates a good correlation with only two screenlines presenting a GEH greater than four. Not withstanding the percentage differences for these screenlines are 10% however it is noted that mention is made to the Christchurch City Council guidelines for model calibration and not the DMRB as stated. DMRB states that in addition to assessing the GEH, screenline flows should be within 5% for all (or nearly all) screenlines. The AM and Inter-peak periods predict approximately 83% of screenlines are within 5%, with the PM peak showing 50%.

The screenlines are however considered to be within acceptable limits given the GEH statistic and that almost all are under 10%. It is worth noting that

Journey Time Calibration

Four journey time routes have been reported. Overall the modelled journey times are predicting faster journey times compared to observed however these are within the DMRB accepted 15%, (with the exception of the Inter-peak Route 3).. The journey time routes are considered short in length, with routes ranging from over 3.5km (Route 1) with the reminder under 800m. It is however noted that the journey times cover the main areas of congestion and given the one way street operation the termination of the routes at particular points enabled the maximum number of runs to be observed.

An important element of the journey time analysis is to ensure sufficient observed journey times are collected to compare with modelled. Additional information was presented stating the number of runs observed for each route. The number of routes is considered acceptable to provide meaningful comparisons.

Journey time graphs have also been presented; these are a good source to assess the journey time route over distance.

Journey time comparisons comparing modelled and observed predict the model to be running faster. It is recommended that this be included in the reporting highlighting in, a deficiency section, and the areas where the journey times are under representing so that future users of the model are aware of the differences.

SCATS Calibration A review of the signal operation has been undertaken. This review concentrates on inspecting signal mapping, firstly checking that each movement has been allocated to the correct signal group and secondly that the appropriate priority has been set.

Signal group mapping appears to have been applied correctly. It was noted that on a number of occasions turning movements which were otherwise unopposed by other vehicle movements and could be seen as


having major priority had been set to medium or minor priority due to conflict with the adjacent pedestrian crossing. This is seen as an appropriate method of replicating delay caused by this conflict in the model environment.

It was noted that the left turn from the Boulcott North approach at Intersection 400 Boulcott/ Willis/ Manners had been allocated to signal group (sg) 4 and should be sg1. This has no bearing on the operation of the model.

Where an automatic demand is not already in operation, pedestrian crossings have been demanded at a number of intersections through the use of variation routines. It is assumed the frequency of introduction of these crossings have been determined in accordance survey data, however some issues with pedestrian introduction are noted at the Elizabeth St/ Kent Tce/ Cambridge Tce intersections as it may have some impact on the intersection operation.

Left turn from the Boulcott North approach at Intersection 400 Boulcott/ Willis/ Manners had been allocated to signal group (sg) 4 and should be sg1

Signal Timing Review

A review of SCATS signal timings was undertaken comparing the modelled signal timings with those observed on-street on the 4th of March 2009. An average run from each peak period was analysed through comparison of the SM data for all subsystem master intersections within the modelled area.

In New Zealand there are currently no calibration criteria guidelines with regard to the representation of traffic signals in models. For the purposes of this review a guide of splits +/- 5% and cycle length +/- 20s was adopted to highlight potential deficiency in this regard. In general the comparison is good however the following deficiencies were identified:

Morning Peak

480 Willis/ Ghuznee: A -6%, B +6% 530 Vivian/ Victoria: A +8%, B -8% 1300 Wellington/ Kilbirnie/ Hamilton: A +5% 430 Victoria/ Dixon: D -12% 510 Ghuznee/ Taranaki: A -6%, C +10% 550 Vivian/ Taranaki: A -6% 425 Dixon/Willis: A +13%, B -6%, C -7% 650 Rugby/ Adelaide: A -6%, B +6%

There is good comparison between modelled and observed cycle lengths in the AM. Concerns relating to cycle lengths for intersections along the ICB route have been addressed along with problems relating to the marriage of intersection 475 to adjacent intersections along Kent Tce/ Cambridge Tce. Remaining deficiencies with splits should be highlighted in the reporting.

Anomalies with phase splits should be highlighted in the reporting

Inter-peak

480 Willis/ Ghuznee: A -6%, D +5% 530 Vivian/Victoria: A +10%, B -10% 450 Taranaki/ Courtney/ Dixon: A +17%, B -13%, E -9% 470 Kent/ Cambridge/ Courtney/ Majoribanks: CL -30s (108 obs, 78 mod) 400 Boulcott/ Willis/ Manners: A -6% 430 Victoria/Dixon: CL -24s (87 obs, 63 mod), A +7%, C +7%, D -14% 510 Ghuznee/ Taranaki: A +8%, C -8%


550 Vivian/ Taranaki: B -6% 1310 Wellington/ Cobham/ Evans Bay: A +16%, C -15%, E -13% (C didn’t run) 425 Dixon/ Willis: B -5% 605 Karo/ Mowon/ Willis/ Abel Smith: B -5%

Deficiencies relating to intersections 470 and 1310 are outlined in the reporting and the reasoning seems sound. As in the AM, anomalies with phase splits at other intersections should be highlighted in the reporting as a deficiency.


Evening Peak

480 Willis/ Ghuznee: A +12%, D -12% 530 Vivian/ Victoria: A -11%, B +11% 470 Kent/ Cambridge/ Courtney/ Majoribanks: CL -24s (119 obs, 95 mod) 430 Victoria/Dixon: D -12% 550 Vivian/ Taranaki: D +10% 1310 Wellington/ Cobham/ Evans Bay: A +12% 650 Rugby/ Adelaide: A -10%, B +10%

Anomalies at intersections 470, 430 and 530 have been identified in the reporting. Inconsistencies relating to phase splits at other intersections should be noted in the reporting.


Queue Length Calibration

The queue length comparison has been undertaken to bring some confidence with the model representing, within acceptable limits, queued vehicles. The definition of a queued vehicle is debatable, however the assessment of the modelled vs. observed brings confidence that the model is representing queues well. It is however noted that grouping queue data together, as presented, does not identify specific areas where the model is performing less than satisfactory and therefore the statistics presented should be viewed with caution.

5.10 Model validation No additional traffic data sets have been reported in the calibration / validation report. Suggest that according to the definition of “validation” in this audit, that no validation has been undertaken.

5.11 Fit for use In the opinion of this audit, with the following recommendations undertaken, the model is fit for use for its intended purpose.

Summary recommendations:

� The models presented are peak hour models only and should be clearly stated in the calibration report as such

� Differences in the standard files between peak hour models to should be highlighted in the reporting � Anomalies with phase splits should be highlighted in the reporting

4-b wellington cbd paramics model validation …...4-b wellington cbd paramics model validation...

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