100212 morpeth traffic model forecasting report rev1
TRANSCRIPT
Transportation
Northumberland County Council September 2011
Morpeth Traffic Model Forecasting Report
Prepared by: .................... Checked by: Gemma Paget Simon Fradgley Consultant Consultant
Approved by: Stuart McNaughton Principal Consultant Morpeth Traffic Model Forecasting Report
Rev No Comments Checked by Approved by
Date
1 Incorporating DfT queries SF SMcN 10/02/10
2 Best and Final Funding Bid SF SMcN 08/09/11 First Floor, One Trinity Gardens, Quayside, Newcastle upon Tyne, NE1 2HF Telephone: 0191 224 6500 Website: http://www.aecom.com Job No 60036225 Reference Rev01 Date Created September 2011 This document is confidential and the copyright of AECOM Limited. Any unauthorised reproduction or usage by any person other than the addressee is strictly prohibited. f:\projects\53101tnet morpeth northern bypass\dev pool modelling\reports\forecasting report\100212 morpeth traffic model forecasting report rev1.docx
1 Introduction ....................................................................................................................................................................... 1
1.1 Background ........................................................................................................................................................... 1
1.2 Report Structure .................................................................................................................................................... 1
2 Model Background ............................................................................................................................................................ 2
2.1 Modelled Time Periods .......................................................................................................................................... 2
2.2 Vehicle Types and Trip Purposes .......................................................................................................................... 2
2.3 Geographical Extent of Model ............................................................................................................................... 2
2.4 Zoning System ....................................................................................................................................................... 2
2.5 Network Description ............................................................................................................................................... 2
2.6 Model Validation .................................................................................................................................................... 3
2.7 Overview of Forecasting Methodology ................................................................................................................... 3
3 Future Year Highway Network ......................................................................................................................................... 4
3.1 Do-Minimum Highway Network ............................................................................................................................. 4
3.2 Do-Something Highway Network ........................................................................................................................... 4
4 Future Year Trip Matrix Development.............................................................................................................................. 5
4.1 Introduction ............................................................................................................................................................ 5
4.2 Background Growth ............................................................................................................................................... 5
4.3 Developments ........................................................................................................................................................ 6
4.4 Trip distribution .................................................................................................................................................... 10
4.5 Future Year Trip Matrix Production ...................................................................................................................... 10
5 Variable Demand Modelling ........................................................................................................................................... 13
5.1 Introduction .......................................................................................................................................................... 13
5.2 Methodology ........................................................................................................................................................ 13
5.3 Impact .................................................................................................................................................................. 18
5.4 Realism Testing ................................................................................................................................................... 19
6 Network Assignment Checks and Characteristics ....................................................................................................... 21
6.1 Generalised Cost Formulation ............................................................................................................................. 21
6.2 Model Convergence ............................................................................................................................................. 21
6.3 Network Wide Characteristics .............................................................................................................................. 24
7 Analysis of Traffic Forecasts ......................................................................................................................................... 25
7.1 Introduction .......................................................................................................................................................... 25
7.2 Analysis of Matrix Totals ...................................................................................................................................... 25
7.3 Analysis of Traffic Flow ........................................................................................................................................ 34
7.4 Analysis of Delay ................................................................................................................................................. 34
7.5 Analysis of Capacity ............................................................................................................................................ 40
7.6 Analysis of Speeds .............................................................................................................................................. 46
7.7 Summary ............................................................................................................................................................. 47
8 Sensitivity Testing .......................................................................................................................................................... 51
8.1 Introduction .......................................................................................................................................................... 51
8.2 Background Growth ............................................................................................................................................. 51
8.3 Uncertainty in Developments ............................................................................................................................... 52
8.4 Analysis of Matrices and Assignment .................................................................................................................. 56
9 Additional Testing ........................................................................................................................................................... 58
9.1 Introduction .......................................................................................................................................................... 58
9.2 Unconstrained Models ......................................................................................................................................... 58
9.3 Off-peak, Weekend and Bank Holiday Models .................................................................................................... 59
10 Summary .......................................................................................................................................................................... 63
10.1 Summary ............................................................................................................................................................. 63
Table of Contents
Appendix A – Scheme .................................................................................................................................................................... 65
Appendix B – Traffic Flow Diagrams ............................................................................................................................................... 66
Appendix C – Location Plan ........................................................................................................................................................... 67
Appendix D – Area Network Plan ................................................................................................................................................... 68
Appendix E – Morpeth Network Plan .............................................................................................................................................. 69
Table 1 - TEMPRO Growth Factors for the Northumberland Authority ......................................................................................5
Table 2 - NTM Growth Factors for North East region ..................................................................................................................5
Table 3 - Database of Proposed Developments ...........................................................................................................................6
Table 4 - Average Trip Rates ....................................................................................................................................................... 10
Table 5 – Volume Scaling Factors For peak periods ................................................................................................................. 15
Table 6: Public Transport Proportions ....................................................................................................................................... 15
Table 7 – Calculation for Value of Time ...................................................................................................................................... 16
Table 8 – Vehicle Occupancy ...................................................................................................................................................... 16
Table 9 – Calibrated Mode Choice Parameters .......................................................................................................................... 16
Table 10 – Calibrated Trip Distribution Parameters ................................................................................................................... 17
Table 11 – 2015 Matrix Totals Before and After the VADMA Process – Do Minimum and Preferred Scheme ...................... 18
Table 12 - 2030 Matrix Totals Before and After the VADMA Process – Do Minimum and Preferred Scheme ...................... 18
Table 13 – Matrix Elasticities ....................................................................................................................................................... 19
Table 14 –Output Fuel Cost Elasticities (network) ..................................................................................................................... 19
Table 15 – Fuel Cost Elasticity Relative to Trip Distribution Parameter .................................................................................. 20
Table 16 – Fuel Cost Elasticity Relative to Mode Choice Parameter ........................................................................................ 20
Table 17 - Highway Assignment Generalised Cost Parameters – 2015 ................................................................................... 21
Table 18 - Highway Assignment Generalised Cost Parameters – 2030 ................................................................................... 21
Table 19 - Summary of Convergence Criteria ............................................................................................................................ 22
Table 20 - Summary of Convergence Statistics – 2015 Do Minimum ....................................................................................... 22
Table 21 - Summary of Convergence Statistics – 2030 Do Minimum ....................................................................................... 23
Table 22 - Summary of Convergence Statistics – 2015 Preferred Scheme ............................................................................. 23
Table 23 - Summary of Convergence Statistics – 2030 Preferred Scheme ............................................................................. 23
Table 24 - Network Statistics – 2015 AM Peak ........................................................................................................................... 24
Table 25 - Network Statistics – 2030 AM Peak ........................................................................................................................... 24
Table 26 - Network Statistics – 2015 Inter-Peak ......................................................................................................................... 24
TAble 27 - Network Statistics – 2030 Inter Peak......................................................................................................................... 24
Table 28 - Network Statistics – 2015 PM Peak ........................................................................................................................... 24
Table 29 - Network Statistics – 2030 PM Peak ........................................................................................................................... 24
Table 30 - 2007 – 2015 Forecasting Process Matrix Totals ....................................................................................................... 26
Table 31 - 2007 – 2030 Forecasting Process Matrix Totals ....................................................................................................... 27
Table 32 - Sectored Growth ......................................................................................................................................................... 28
Table 33 - Sectored Growth ......................................................................................................................................................... 29
Table 34 - Sectored Growth ......................................................................................................................................................... 30
Table 35 - Sectored Growth ......................................................................................................................................................... 31
Table 36 - Sectored Growth ......................................................................................................................................................... 32
Table 37 - Sectored Growth ......................................................................................................................................................... 33
Table 38 - Forecast Traffic Flows – AM Peak Period ................................................................................................................. 48
Table 39 - Forecast Traffic Flows – Inter Peak Period ............................................................................................................... 49
Table 40 - Forecast Traffic Flows – PM Peak Period ................................................................................................................. 50
Table 41 - Pessimistic and Optimistic Growth Factors for the Castle Morpeth Authority ..................................................... 51
Table 42 – 2007-2030 Growth Rates ............................................................................................................................................ 52
Table 43 - Planned Developments in Modelled Area – Uncertainty Log ................................................................................. 52
Table 44 – 2015 Post-Variable Demand Sensitivity Totals ........................................................................................................ 56
Table 45 – 2030 Post-Variable Demand Sensitivity Totals ........................................................................................................ 57
Table 46: 2007-2015 TEMPRO/Development growth comparison (Castle Morpeth) ............................................................... 58
Table 47: 2007-2030 TEMPRO/Development growth comparison (Castle Morpeth) ............................................................... 59
Table 48: Proposed Methodology for Forecasting .................................................................................................................... 59
Table 49: Off-Peak, Weekend and Bank Holiday Factors .......................................................................................................... 61
Figure 1: Flow Diagram Detailing the Forecasting Process ..................................................................................................... 12
Figure 2 - Variable Demand Procedure ....................................................................................................................................... 14
Figure 3 – AM 2030 Do Minimum Delay ...................................................................................................................................... 35
Figure 4 – AM 2030 Do Something Delay ................................................................................................................................... 36
Figure 5 – IP 2030 Do Minimum Delay ........................................................................................................................................ 37
Figure 6 – IP 2030 Do Something Delay ...................................................................................................................................... 38
Figure 7 – PM 2030 Do Minimum Delay ...................................................................................................................................... 39
Figure 8 – PM 2030 Do Something Delay .................................................................................................................................... 40
Figure 9 – AM 2030 Do Minimum Capacity ................................................................................................................................. 41
Figure 10 – AM 2030 Do Something Capacity ............................................................................................................................ 42
Figure 11 – Inter-Peak 2030 Do Minimum Capacity ................................................................................................................... 43
Figure 12 – Inter-Peak 2030 Do Something Capacity ................................................................................................................ 44
Figure 13 – PM 2030 Do Minimum Capacity ............................................................................................................................... 45
Figure 14 – PM 2030 Do Something Capacity ............................................................................................................................ 46
Figure 15: Off-Peak, Weekend and Bank Holiday Forecasting Methodology .......................................................................... 62
AECOM Morpeth Traffic Model Forecasting Report 1
Capabilities on project:
Transportation
1.1 Background
Northumberland County Council (NCC) has long had a desire to see the construction of a link road between the A1 and
South East Northumberland having first appeared in local policy documents in the mid 1990’s. Following advice from
Government Office in 2001, the proposal was split into three parts; the A1-South East Northumberland Link Road-
Morpeth Northern Bypass (A1-SENSLR-MNB) is the only section still to be progressed.
The construction of the A1-SENSLR-MNB is expected to lead to the following benefits:
- Reduce congestion in Morpeth town centre;
- Improve accessibility to South East Northumberland;
- Facilitate development on land to the north of Morpeth.
This report summarises the methodology which has been adopted in order to assess the future impacts of the proposed
link road. The main objective of the Forecasting Report is to describe the development of the future year traffic model to
enable operational, economic and environmental evaluation of the proposed A1-SENSLR-MNB. This evaluation has
been undertaken through comparison of the Do Minimum reference case and the Do Something test case scenarios.
1.2 Report Structure
Following this introductory section, this report has been prepared with the following structure:
- Section 2 provides a background to the model and the approach to forecasting.
- Section 3 covers the future highway network conditions.
- Section 4 deals with the forecast trip matrix production.
- Section 5 provides details of the variable demand process.
- Section 6 covers characteristics of the network assignment and checks made on the assignments.
- Section 7 details an analysis of the forecasting results.
- Section 8 provides an explanation of the sensitivity testing.
- Section 10 provides information on additional models which have been constructed.
- Section 9 provides a summary to the report.
1 Introduction
AECOM Morpeth Traffic Model Forecasting Report 2
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2.1 Modelled Time Periods
Three base year models have been developed representing a Monday to Thursday average for the following time
periods:
- 2007 Morning Peak (0800-0900);
- 2007 Inter-Peak (1000-1600) – a single inter-peak matrix represents an average hour; and
- 2007 Evening Peak (1700-1800)
This is discussed in greater detail in the Morpeth Traffic Model Local Model Validation Report, July 2011.
2.2 Vehicle Types and Trip Purposes
Demand matrices have been produced for 4 different user classes for input into the network. The first 3 consist of the
Car/LGV class spilt down into 3 journey purposes to reflect differing values of time and distance. The 4th and final user
class is for medium and heavy goods vehicles. The input matrix is split as follows:
- User class 1 (cars and light goods vehicles - commuting); and
- User class 2 (cars and light goods vehicles - business); and
- User class 3 (cars and light goods vehicles - other); and
- User class 4 (medium and heavy goods vehicles)
2.3 Geographical Extent of Model
The overall study area is sufficient to ensure an accurate representation of the longer distance journeys on major
strategic routes in the region although focuses on the town of Morpeth and the surrounding area. The study area, as
shown in Appendix C, Appendix D and Appendix E, is bounded by:
- A1/A1068 at Alnwick to the north
- the A1068 and A189 to the east
- the A19 south of Cramlington to the south
- A1 to the west
2.4 Zoning System
The zone system is in part defined by the level of detail provided within the network. The level of detail provided in the
network away from the main areas of interest determined the level of disaggregation required within the zoning system.
Within the core study area zones are defined by individual output area with aggregation of output area with distance from
the scheme. This resulted in a model with 81 zones.
The simulation junctions are divided into:
- 45 external nodes;
- 56 priority junctions;
- 10 roundabouts; and
- 1 traffic signal
More detail on the zoning system and extent of the model can be found in the Morpeth Traffic Model Local Model
Validation Report, July 2011.
2.5 Network Description
The model consists of both simulation (core) and buffer area. The simulation network is coded in considerable detail
using junction based data in addition to link based data. The simulation network is surrounded by the buffer network,
which is coded in less detail with data describing only the characteristics of the links.
2 Model Background
AECOM Morpeth Traffic Model Forecasting Report 3
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The simulation area consists of the Morpeth town centre area, the A192 and A197 routes and the A196 and A1 to the
east and west of the town respectively. This enables major delays occurring within and around the town centre to be
reflected.
The remainder of the study area covers all major strategic routes into the greater zone of influence. This area has been
modelled in less detail and forms the buffer network.
2.6 Model Validation
The Morpeth Traffic Model Local Model Validation Report demonstrated that overall, the base year Morpeth model was a
sufficiently robust model that reproduces the existing situation and is suitable as a basis for forecasting.
Forecasts have therefore been produced to provide input into the following processes:
- Scheme design;
- Environmental assessment; and
- Economic cost benefit analysis
2.7 Overview of Forecasting Methodology
The forecasting work has been undertaken in accordance with current WebTAG guidance including a variable demand
assessment.
Networks and trip demand matrices were developed for the following forecast years:
- 2015 being the proposed year of opening for the A1-SENSLR-MNB; and
- 2030 being the proposed design year, 15 years after the opening of the A1-SENSLR-MNB.
To reflect future change in travel patterns, proposed employment and residential developments were incorporated into
the future year highway networks. No committed highway schemes have been identified and therefore the Do-Minimum
highway network remains unchanged.
The growth factors for future year demand were derived from TEMPRO and NTM. Account was also taken of local
developments at various stages of planning status.
The effect of induced/generated traffic was modelled using a freestanding variable demand modelling process that has
been developed by AECOM, and used in previous work with the approval of the DfT.
AECOM Morpeth Traffic Model Forecasting Report 4
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3.1 Do-Minimum Highway Network
Officers from Northumberland County Council were consulted for information on any committed highway schemes likely
to impact on traffic patterns across the region. It was confirmed that there were no committed highway schemes of
significance in the area. As such, the Do-Minimum highway network was assumed to be the same as the base model.
3.2 Do-Something Highway Network
The Preferred Option involves the construction of a 3.7km length of 7.3m wide single carriageway between the A1 east
of Mitford and the A197 Pegswood Bypass. The scheme also incorporates a cycleway and footway for the full length of
the route. The new road will tie in as a fifth arm at the recently constructed Whorral Bank roundabout located west of
Pegswood. The scheme incorporates the construction of an all movements grade-separated junction onto the A1 at St
Leonard’s and the construction of two at-grade junctions on the St George’s Link section of the Bypass: the Northgate
roundabout will provide a junction with the A192 west of Fulbeck; and St George’s Roundabout, at a point north west of
St George’s hospital, will provide an access point to a future development (St George’s Phase 2 and Phase 3). The
scheme is detailed in Appendix A.
3 Future Year Highway Network
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4.1 Introduction
In order to predict traffic growth in future year scenarios, a number of different sources of data were used to provide
information on growth and development which would impact on traffic levels in the modelled area.
NCC provided information on proposed developments in the study area and the TRICS database (2011a) was used to
obtain appropriate production and attraction trip rate factors. TEMPRO, the National Trip End Model (NTEM) and NTM,
the Department for Transport’s Nation Transport Model, were used to produce background traffic growth forecasts as
follows:
- TEMPRO (version 6.2) was used to produce growth factors for car trip and light good vehicle demand matrices;
- NTM (2009) was used to produce growth factors for trips made by medium and heavy good vehicles.
4.2 Background Growth
4.2.1 Light Vehicles
TEMPRO and NTM factors have been used to calculate the background growth within the modelled area, for lights and
heavy vehicles respectively.
Local TEMPRO factors have been used for light traffic (User Classes 1, 2 and 3) growth, which takes into account local
demographic change, socioeconomic variation and changes in modes as well as other factors that affect the growth of
traffic within the locality.
Traffic growth factors for car trips were extracted from the TEMPRO database (version 6.2) for AM, inter-peak and PM
periods for the authority of Northumberland in the following time periods:
- 2007-2015
- 2007-2030
The results from TEMPRO are detailed in the below table:
Table 1 - TEMPRO Growth Factors for the Northumberland Authority
Time Period 2007-2015 2007-2030
Origin Destination Origin Destination
AM Peak 1.003 1.036 1.028 1.059 Inter-Peak 1.059 1.056 1.138 1.132
PM Peak 1.035 1.015 1.070 1.052
4.2.2 Heavy Vehicles
The base year heavy goods vehicle matrices have been growthed up for each of the future years using factors derived
from the 2009 forecast results from the DfT’s National Transport Model. The 2009 report supplies national growth factors
from a base year of 2003 to future years of 2015, 2025 and 2035 for heavy traffic.
Factors for the 2015 and 2030 forecast years were obtained by interpolating between 2003 and 2035. For both cases,
linear growth was assumed in order to calculate the years which were not specifically modelled within NTM.
The NTM growth forecasts are split into different regions and are universal across the day, hence the same factors have
been applied to all of the time periods within the model and the same value applied to both origin and destination. The
NTM growth factors used are supplied in Table 2 below:
Table 2 - NTM Growth Factors for North East region
NTM Period Calculated Factor
2007 – 2015 1.039
2007 - 2030 1.240
4 Future Year Trip Matrix
Development
AECOM Morpeth Traffic Model Forecasting Report 6
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4.3 Developments
4.3.1 Development Data
A list of all proposed developments in the desired area which were forecast to be completed by 2030 was provided by
NCC. Each development was assigned a land use and trip rate and, using the TRICs software, factors for arrivals and
departures were calculated dependent on size of the development. It was not considered that future developments in
districts outside of the buffer network would have a significant impact on trip rates due to the wide area incorporated by
the buffer network. A list of the proposals included in the development database is shown in Table 3 below.
Table 3 - Database of Proposed Developments
Site No.
Site Name Proposed Land Use
Area (m2)
Size of Development
A (Retail) (sq.m)
B (Comm. >1000 (sq.m)
C - Residential D
Other (Sq.m) HA
No of Res. Units
1 Hadston Industrial Estate
Employment 2700
3039
2 Morpeth Fairmoor (Northgate)
Employment 100800
40800
3 Morpeth Fairmoor (Northgate)
Residential 101000
192
4 Longhorsely Land at East Road
Residential 3800
12
5 Morpeth Ex to Land Fairmoor
Employment 56000
22400
6 Morpeth Fairmoor Adj to A1
Employment 78800
31520
7 Morpeth Station Yard Employment 17400
6960
8 Stannington, part St. Mary's Hospital (mixed use)
Residential 283900
172
9 Stannington, part St. Mary's Hospital (mixed use)
Employment 283900
4924
10 Ellington Colliery (mixed Use)
Employment 146800
4185
11 Ellington Colliery (mixed Use)
Residential 146800
300
12 Lynemouth Colliery (mixed Use)
Residential 146300
200
13 Lynemouth Colliery (mixed Use)
Employment 146000
32700
14 Low Stanners Morpeth mixed development
Retail 22800 4560
15 Goose Hill Factory site/ Davidsons Garage Morpeth
Retail 1900 645
16 Goose Hill Factory site/ Davidsons Garage Morpeth
Residential 1900
60
17 Stobswood Brickworks Residential 75500
149
AECOM Morpeth Traffic Model Forecasting Report 7
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Site No.
Site Name Proposed Land Use
Area (m2)
Size of Development
A (Retail) (sq.m)
B (Comm. >1000 (sq.m)
C - Residential D
Other (Sq.m) HA
No of Res. Units
18 St Georges,Morpeth Phase 1
Residential 115000
246
19 St Georges,Morpeth Phase 2
Residential 319300
693
20 St Georges,Morpeth Phase 3
Residential 343500
241
21 Hepscott Park Employment 81800
32720
22 Hepscott Park Residential 81800
75
23 Park View, Hadston (Phase 3) West of A1068
Residential 28200
86
24 NCB Workshop site Ashington
Residential 96300
339
25 ASDA, Lintonville Terrace, Ashington
Retail 22000 6789
26 South of Wansbeck General Hospital, Ashington
Residential 547800
628
27 Ashwood Business Park, North Seaton
Employment 402400
3718
28 Wansbeck Business Park, Ashington
Employment 193300
21111
29 Lintonville Enterprise Park, Ashington
Employment 36000
6139
30 Former Ashington Hospital, Station Road
Residential 30200
139
31 Existing Northumberland College
Residential 79600
337
32 Ellington Colliery (site offices)
Employment 9500
951
33 Northumberland College (Hawthorne Annexe), Ashington
Residential 7900
47
34 South Loansdean, Morpeth (SHLAA-3007)
Residential 104300
240
35 NCC sites Fire Station, County Hall adjoining land
Residential 45900
150
36 Stobhill South Residential 114200
400
37 South Shore Links Road, Blyth
Residential 60300 229
38 Land at Wheatridge Park, Seaton Delaval
Residential 75900 187
39 Land at area 2A Chase Farm Drive Blyth
Residential 20300 83
AECOM Morpeth Traffic Model Forecasting Report 8
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Site No.
Site Name Proposed Land Use
Area (m2)
Size of Development
A (Retail) (sq.m)
B (Comm. >1000 (sq.m)
C - Residential D
Other (Sq.m) HA
No of Res. Units
40
Land at West Blyth accessed from Chase Farm Drive Blyth (Phases 1&2)
Residential 150800 443
41
Land at West Blyth accessed from Chase Farm Drive Blyth (Phase 3)
Residential 78000 258
42 Asda Stores Limited, Cowpen Road, Blyth
Retail 41300 1039
43 Tesco Supermarket Market Place Bedlington
Retail 23900 2338
44 Morrisons, Regent Street, Blyth
Retail 21300 2130
45 Narec Test Site, Albert Street, Blyth
Employment 10100 4040
46 Narec Test Site Albert Street, Blyth
Employment 30000 12000
47 Queen Street, Amble Residential 48900 46
48 Queen Street, Amble Retail 48900 2747
49 A1068 (land west of) and Marks Bridge (land south of) Amble
Residential 88000 260
50 Coquet Enterprise Park, Amble
Employment 1700 700
51 Land at Crofton Mill Industrial Estate, Blyth
Residential 20600 79
52 Crossland Park, Cramlington
Employment 64400 4079
53 Amble Boat Co. Amble - Residential
Residential 10900 127
54 Amble Boat Co. Amble - Employment
Employment 10900 1000
55 Amble Boat Co. Amble - Retail
Retail 10900 1000
56 Land East of A189 and South of Lanercost Park, Cramlington
Hospital 213100 85240
57 West Hartford Business Park Cramlington
Employment 527600 211040
58 South West Sector Cramlington
Residential 1240000 1000
59 Sanderson Arcade Morpeth
Retail 35200 8957
AECOM Morpeth Traffic Model Forecasting Report 9
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Site No.
Site Name Proposed Land Use
Area (m2)
Size of Development
A (Retail) (sq.m)
B (Comm. >1000 (sq.m)
C - Residential D
Other (Sq.m) HA
No of Res. Units
60 The Kylins, Morpeth Residential 24200 88
61 East Ashington SPD Area
Employment 36100 363
62 East Ashington SPD Area
Retail 36100 2157
63 Jubilee Industrial Estate
Employment 6460 2584
64 North Seaton Industrial Estate
Employment 59650 23860
65 West Sleekburn Industrial Estate
Employment 21200 8480
66 Cambois Residential 526400 52.64
67 Welbeck Terrace Pegswood
Residential 30400 78
68 The Mount, Morpeth Non-residential 6400 3644
69 Land east of Whorral Bank Roundabout Morpeth
Non-residential 13800 1044
70 Northgate Hospital (SHLAA 3079)
Residential 286200 250
Each development was assigned to a particular zone in the network which matched the location of the site. Some of the
developments were in zones outside the detailed zoning system of Morpeth town centre and near to other urban areas.
In these cases, it was assumed that not all of the trips relating to these developments would be travelling through the
simulation network areas and, due to the larger zone coverage, there would be a significant amount of intrazonal trips.
To account for intrazonal trips, or trips which would not access the modelled network, where possible, information was
sought from detailed Transport Assessments for these developments. Zone 844, to the far east of the model contains
developments 10 to 13. The outline planning applications for these developments, the Lynmouth Outline Planning
Application and the Ellington Outline Planning Application, both February 2009 and produced by Entec, were available
and the agreed distribution from these documents suggests that no more than 10% of the potential traffic from these
developments should be entering the Morpeth modelled network.
A number of the developments identified in Table 3 are located in Ashington and Blyth. In order to account for trips from
these zones travelling to other areas or intrazonally, the number of trips was reduced to 25%. Where development sites
are located in Cramlington, the number of trips was reduced by 10%, which reflects the fact that trips to and from these
zones are unlikely to have been captured in the Roadside Interview Surveys.
As previously mentioned, trip rate figures were calculated separately for each development type. Vehicle trip rates were
calculated based on similar developments in the TRICS database (2011a).
Trip rates are listed in Table 4 below.
AECOM Morpeth Traffic Model Forecasting Report 10
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Table 4 - Average Trip Rates
Land Use Sub Land Use
Trip Rate
Units AM Peak Inter Peak PM Peak
Arr. Dep. Arr. Dep. Arr. Dep. Employment Office 0.01 0.003 0.003 0.003 0.002 0.011 Trips per 100m
2 GFA
Employment Industrial Estate
0.005 0.002 0.003 0.003 0.001 0.004 Trips per 100m2 GFA
Employment Industrial Unit
0.003 0.001 0.002 0.002 0.000 0.003 Trips per 100m2 GFA
Hotel, Food & Drink
Hotel 0.005 0.006 0.003 0.003 0.004 0.003 Trips per 100m2 GFA
Residential Hospital 0.008 0.002 0.004 0.004 0.002 0.006 Trips per 100m2 GFA
Residential Houses Privately Owned
0.18 0.45 0.2 0.19 0.4 0.23 Trips per dwelling
Residential Houses Privately Owned
4.65 11.68 5.22 4.95 10.25 6.14 Trips per hectare
Leisure Mixed Leisure Complex
0.006 0.004 0.006 0.006 0.018 0.013 Trips per 100m2 GFA
Non-Residential
GP Surgery 0.028 0.010 0.013 0.013 0.015 0.026 Trips per 100m2 GFA
Non-Residential
Vets 0.028 0.013 0.029 0.024 0.035 0.040 Trips per 100m2 GFA
Retail Superstore 0.029 0.019 0.053 0.053 0.052 0.054 Trips per 100m2 GFA
Retail Shopping Centre
0.037 0.032 0.039 0.039 0.036 0.036 Trips per 100m2 GFA
The development database contains information on the size of each proposed development within the study area.
However, in most cases this was provided in the form of land available for development. It was assumed that some of
this available land will be designated for car parking or landscaping. Therefore it was estimated that the actual footprint
of the development buildings would be 40% of the total land area.
4.4 Trip distribution
For the majority of zones contained within the model, no developments were specified. In these cases, forecast year
distributions for future growth were based on the existing trip distributions for the zone.
For zones where developments were specified, existing base year distributions were assessed for applicability in terms
of land use. Where base year distributions would not reflect those associated with forecast year developments, the trip
distribution from an adjacent base year zone with a similar land-use was applied.
4.5 Future Year Trip Matrix Production
It is a requirement as stated in DMRB and WebTAG 3.15.2 that there is a need to control overall growth to TEMPRO.
Therefore, adjustment factors were calculated and applied such that the overall growth was constrained to local
TEMPRO factors. Origin and destination trip end totals were then balanced in order to enable the matrix furness
procedure to be carried out successfully.
Matrices were then furnessed to the revised row and column totals using the MX facility within the SATURN suite of
programs. Each future year matrix was then ready to be fed through the variable demand process as discussed in
Section 5.
The TEMPRO database takes into account potential for developments within each region but does not consider any
specific planned developments. Since the methodology for the scheme will include several actual developments in the
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area, the TEMPRO forecasts and specific development traffic will need to be combined whilst maintaining TEMPRO
growth to avoid double counting.
In order to constrain the growth of the matrices to the TEMPRO factors, a methodology from previous work undertaken
by AECOM has been applied. This methodology involves the following:
- Adding the base year 2007 row and column totals to the proposed development traffic (a)
- Factoring the base year 2007 row and column totals by the TEMPRO factors (b)
- Factoring the base year + development traffic by the TEMPRO factors (c)
- Dividing the total of (b) by the total of (c) and multiplying by (c)
The above method constrains the development traffic to the TEMPRO factored row and column totals for each year and
time period. Once the new row and column totals were calculated for each of the matrices, each matrix was furnessed
within the SATURN program and the final matrices output to be transferred in to the variable demand process. See
Chapter 5 for details
These final matrices for 2015 and 2030, AM, inter-peak and PM therefore contain both general background and specific
development growth constrained back to the approved TEMPRO overall growth rates for the region.
The forecasting process is illustrated in the following diagram.
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Figure 1: Flow Diagram Detailing the Forecasting Process
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5.1 Introduction
When a scheme is opened a range of responses by road users can take place, which can include all or some of the
following:
- Reassignment;
- Trip retiming;
- Trip redistribution;
- Mode switch;
- Change vehicle occupancy;
- Increase the frequency of some journeys;
- Trip Generation; and
- Change the pattern of land use.
A scheme which provides extra capacity on the road network can lead to traffic being induced through any of the above
responses.
In the same way, if there is a lack of capacity on the network (e.g. such as in the Do-Minimum when no scheme is
implemented), traffic can be suppressed.
To take account of the impacts of future year traffic conditions a full variable demand modelling (VDM) approach has
been taken in developing the future year matrices. This section describes the methodology adopted for the VDM and
describes the results of the approach by presenting a comparison of the demand matrices before and after the VDM was
applied.
5.2 Methodology
A freestanding variable demand modelling process has been developed for the Morpeth model.
This approach is fully compliant with the Department for Transport’s variable demand guidelines. The process used for
the Morpeth project has been based on a similar model developed previously by AECOM and approved by the
Department for Transport.
The process consists of a series of iterations during which the current demand matrices are assigned, skimmed cost
matrices are extracted and based on comparative travel costs the demand matrices are updated. The full process is
illustrated in Figure 2.
Key elements of the model
- Traffic assignments are carried out using SATURN, matrix manipulation and calculation is carried out in Emme/2
- Public transport costs are fixed within the process and have been assumed to remain constant across all scenarios
- All model parameters are based on the Webtag (Unit 3.10.3) Variable Demand Modelling advice (June 2006).
- Convergence of the model is measured by reference to changes in overall costs using the functions defined in
Webtag. (Unit 3.10.4)
- The model pivots on the base year assignment, so that all future year cost changes are compared against the base
year costs to determine changes in demand patterns.
- The following responses can be modelled:
o Mode Choice (car v public transport)
o Time Choice
o Distribution
o Trip frequency
o Responses are modelled separately for each trip purpose
5 Variable Demand Modelling
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Figure 2 - Variable Demand Procedure
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5.2.1 Input Matrices
The assignment matrices output from the initial future year growth process are peak hour matrices. For the purpose of
the demand model, the peak hours have been factored to periods and thus to an overall 12 hour matrix. The matrices
used in the process are origin – destination rather than production – attraction matrices.
Factors to produce the 12 hour matrix have been derived from ATC data as below in Table 5
Table 5 – Volume Scaling Factors For peak periods
The Morpeth model holds car demand matrices in the below three trip purposes:
- Commuting
- Business
- Other
For the purposes of the demand model it was necessary to break down the business and other trips into home based
and non home based matrices. This was done by applying global factors to the matrices in the assignment model.
On the basis of 2006 trip end data for the Morpeth area in Tempro, 65% of business trips were assumed to be home
based, and for other personal trip purposes 85% were assumed to be home based.
Intrazonal trips are not excluded from the process and there is the potential for trips to be interchanged between
intrazonal and interzonal as a result of the process. The intrazonal costs are calculated as half of the row minimum,
excluding zeros.
In this variable demand process external to external and external to internal trips have been frozen, and are thus not
affected by the variable demand process.
The following model zones are defined as external zones for this purpose.
823, 824, 825, 827, 831, 837, 850 - 854
Internal to external trips remain unfrozen.
5.2.2 Public Transport Trips
There were no public transport surveys, and no public transport model, included as a part of the Morpeth model.
To seed the mode choice model a baseline number of public transport trips were needed. Tempro 6.1 was used to
examine the number of public transport trips, as a proportion of all trips, in the Morpeth area. These proportions were
used to calculate the number of base year public transport trips from the numbers of car trips and are shown in Table 6
below.
Table 6: Public Transport Proportions
Peak Hour Peak Period Factor
0800 – 0900 0700 – 1000 2.824
Average inter peak 1000 – 1600 6.000
1700 – 1800 1600 – 1900 2.751
% PT Trips
Commuting 6.7%
Business 1.0%
Other 12.3%
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It was assumed that 50% of these public transport trips would have a car available for the journey. Base year public
transport times were globally assumed to be 25% greater than the equivalent highway journey times. All tests are based
on the difference between base and test journey times, and for all tests this was assumed to be zero.
5.2.3 Travel Cost Assumptions
Values of time used in the model are taken from WebTAG 3.5.6. The calculations used to adjust the 2002 based
WebTAG values to 2006 base year values are shown below in Table 7:
Table 7 – Calculation for Value of Time
WebTAG Value 2002 Change 2002 – 2006
Model input values
£/hr (2002) pence/min (2002) % pence/min (2006)
HBW 5.04 8.40 +8.56 9.12 HBEB 21.86 36.43 +10.77 40.36
HBO 4.46 7.43 +8.56 8.07 NHBEB 21.86 36.43 +10.77 40.36
NHBO 4.46 8.07 +8.56 8.07
National average values for vehicle occupancies have been used within the model. These have been derived from
applied from WebTAG 3.5.6 and are shown below in Table 8.
Table 8 – Vehicle Occupancy AM Peak Inter Peak PM Peak
HBW 1.114 1.096 1.104 HBEB 1.224 1.162 1.156
HBO 1.652 1.635 1.705 NHBEB 1.224 1.162 1.156
NHBO 1.652 1.635 1.705
WebTAG Table 4 corrected to 2006 values using WebTAG table 6
5.2.4 Final Car Trip Distribution Lambda Values
Fuel costs have been calculated using the fuel VOC formulae parameter values included in Table 10 of Unit 3.5.6. These
parameters have been used to calculate litres per kilometre. The fuel consumption has then been multiplied by the
average fuel costs included in Table 11 of Unit 3.5.6. Fuel costs for 2006 were used in the model, with non work trips
incurring the full cost, while in work trips incurred only the resource and duty costs. Within the model costs were then
reduced to take account of the fuel efficiency improvements included in Unit 3.5.6 Table 13.
5.2.5 Calibrated Parameter Values
The parameter values for the main mode choice model are shown below, together with the suggested values included in
WebTAG Unit 3.10.3. Table 9 below shows that for the non work purposes the calibrated values fall within the
recommended range. For the non home based employers business trip purpose there is little data available in WebTAG,
and no range is provided. A value lower than the single value contained in WebTAG range was found to produce a
better calibration.
Table 9 – Calibrated Mode Choice Parameters
Purpose WebTAG minimum
WebTAG maximum
Calibrated Values
HBW 0.50 0.83 0.50
HBEB 0.26 0.65 0.65 HBO 0.27 1.00 0.53
NHBEB 0.73 0.73 0.53 NHBO 0.62 1.00 0.71
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The parameter values for the trip distribution model are shown below, together with the suggested values included in
WebTAG Unit 3.10.3. Table 10 below shows that for the non work purposes the calibrated values fall within the
recommended range. For the in work trips parameter values slightly above the WebTAG range were found to produce a
better calibration.
Table 10 – Calibrated Trip Distribution Parameters Purpose WebTAG
minimum WebTAG maximum
Calibrated Values
HBW 0.054 0.113 0.100 HBEB 0.038 0.106 0.150
HBO 0.074 0.160 0.090
HNBEB 0.069 0.107 0.150 NHBO 0.073 0.105 0.080
5.2.6 Convergence Stability
The convergence of the variable demand process was measured using the approach outlined in WebTAG. This is based
on calculating the demand/supply gap using the following function on each iteration of the process.
Where:
Xijctm is the current flow vector or matrix from the model
C(Xijctm) is the generalised cost vector or matrix obtained by assigning that matrix
D(C(Xijctm)) is the flow vector or matrix output by the demand model, using the costs C(Xijctm) as input
ijctm represents origin i, destination j, demand segment/user class c, time period t and mode m
The process is assumed to have converged when the demand/supply gap falls below 0.15% for each user class in each
time period.
In addition, the convergence of each SATURN run during the process is measured. In each case the SATURN model is
run until the following levels of convergence are reached.
The target for convergence stability is 99% of link flows change by less than 5% on four consecutive iterations.
In the current version of the process, smoothing is applied to demand rather than costs.
The smoothing process begins after three iterations of the model. The function used to calculate the smoothed matrices
is:
Demandn = 2 * demandn + (n-3) * demandn-1 (n-1) (n-1)
Where:
Demandn is the demand matrix at the end of the nth iteration
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Convergence of the demand –supply model is measured by the criterion identified in WebTAG Unit 3.10.4. The model is
run until all trip purposes, in all time periods have a gap value lower than 0.05%. This is lower than the 1%
recommended in WebTAG, but is achievable in this case, due to the simple nature of the network.
5.2.7 Convergence Proximity
Delta values for each run are checked to ensure that they are less than 1%. In most cases delta is significantly lower,
typically around 0.15%.
5.3 Impact
In order to fully understand the impact of applying a variable demand modelling approach, the pre-VDM and post-VDM
matrices for Car trips have been compared for the Do Minimum and Do Something scheme scenarios. Only Car trips
have been considered as these are subject to the greatest change as a result of the variable demand process, with little
or no change affecting other user classes.
The results of this analysis are presented below, and are discussed along with a direct comparison between the variable
demand Do Minimum and Do Something Scheme models, which will show the effect of the variable demand process on
Car trips.
5.3.1 Comparison of Matrix Totals
Table 11 and 12 below, provide a summary of matrix totals for Car trips across the modelled network for all peak periods
in the opening year 2015 and design year 2030.
Table 11 – 2015 Matrix Totals Before and After the VADMA Process – Do Minimum and Preferred Scheme
Time Period 2015 Base Forecast
Do Minimum – 2015 (1) Preferred Scheme – 2015 (2) % Change between (2) & (1) Demand
% Change to Base
Demand % Change to
Base
AM Peak 21,240 21,401 0.76% 21,435 0.92% 0.16%
Inter Peak 10,924 11,125 1.84% 11,125 1.84% 0.00%
PM Peak 24,418 24,516 0.40% 24,603 0.76% 0.35%
Total 56,582 57,042 0.81% 57,163 1.03% 0.21%
Table 12 - 2030 Matrix Totals Before and After the VADMA Process – Do Minimum and Preferred Scheme
Time Period 2030 Base Forecast
Do Minimum – 2030 (1) Preferred Scheme – 2030 (2) % Change between (2) & (1) Demand
% Change to Base
Demand % Change to
Base
AM Peak 21,749 22,029 1.29% 22,121 1.71% 0.42%
Inter Peak 11,722 12,096 3.19% 12,133 3.51% 0.31%
PM Peak 25,276 25,491 0.85% 25,596 1.27% 0.41%
Total 58,747 59,616 1.48% 59,850 1.88% 0.39%
The results indicate that in 2015 the variable demand process is having the effect of increasing demand in both the Do
Minimum and Do Something Scheme variable demand models, compared with the Base forecast. This is due to the real
terms increases in earnings and decreases in vehicle operating costs between the base year and the forecast year.
These changes are introduced into the forecasts as a part of the variable demand model. Overall, both models
experience very similar changes in traffic with the % difference between the DS and DS increase being less than 1%.
The results show that in the 2030 future year scenario, both the Do Minimum and Do Something Scheme models exhibit
a noticeable increase in total car trips compared with the 2030 Base forecast. The variable demand process has the
effect of increasing demand by approx 1 to 2% in the AM and PM and approx 3% in the Inter Peak across both the Do
Minimum and Do Something Scenarios.
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Comparing both the Do Minimum post-VDM and Do Something Scheme post-VDM model results indicates that, in 2030,
the introduction of the scheme will induce additional car trips onto the network. The total number of trips induced by the
scheme remains relatively small with an increase in the Preferred Scheme of around 0.42% to 0.41%, in the AM and PM
peak periods.
5.4 Realism Testing
This section presents the results of the revised realism tests.
5.4.1 Fuel Cost
Fuel cost elasticities were determined by running the model with a 10% fuel cost increase. The results were obtained
from a fully converged model run. The matrix elasticities to a 10% increase in fuel costs produced by the model are
shown below.
Table 13 – Matrix Elasticities
Purpose
Car Fuel Cost Elasticities (matrix calculation)
Morning Peak Inter Peak Evening Peak 12-Hour
HBW -0.20 -0.41 -0.23 -0.25
HBEB -0.05 -0.11 -0.09 -0.09
HBO -0.29 -0.40 -0.20 -0.32
NHBEB -0.04 -0.13 -0.09 -0.10
NHBO -0.28 -0.40 -0.18 -0.32
Overall -0.22 -0.33 -0.20 -0.28
The current version of WebTAG 3.10.4 recommends that elasticity values should be expected to fall within the range -
0.1 to -0.4, with an overall elasticity of around 0.3. The discretionary trip purposes should be closer to -0.4 and business
trips closer to -0.1.
The results show that the weighted 12 hour results fall into the range identified within WebTAG.
The new consultation version of WebTAG narrows the recommended gap to a range of between -0.25 and -0.35. The
weighted 12 hour values for non work trips can be seen to also fall within this narrower band.
5.4.2 Network Based Fuel Cost
A set of network based fuel cost elasticities have also been calculated. These were obtained using the total network
vehicle kilometres on all links, excluding centroid connectors. As such, the calculations include the external to external
and external to internal trips which are not included in the variable demand model. As such, this calculation will tend to
underestimate the elasticities; however there was no readily available method of excluding these trips. It should be noted
that the assignment combines the home based and non home based matrices for the business and other trip purposes,
so combined elasticities are calculated for these purposes.
Table 14 –Output Fuel Cost Elasticities (network)
Purpose
Car Fuel Cost Elasticities (matrix calculation)
Morning Peak Inter Peak Evening Peak 12-Hour
Commute -0.11 -0.19 -0.12 -0.13
Business -0.03 -0.06 -0.05 -0.05
Other -0.18 -0.17 -0.09 -0.15
Overall -0.13 -0.14 -0.13 -0.13
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The results show the relative scales of the elasticity between trip purposes are retained. However, as would be predicted
the absolute values are lower than obtained for the matrix based calculation.
5.4.3 Journey time
Journey time elasticities were determined by running the model with a 10% increase in journey times. The results were
obtained from a single run of the demand model. The matrix elasticities to a 10% increase in highway journey time
produced by the model are shown below.
Table 27 – Output Journey Time Elasticities
WebTAG’s guidance on elasticity with respect to journey time suggests that that journey time elasticities will vary
considerably more than fuel cost elasticities and that there is no recommended range for response to journey time.
The results show that the elasticities are considerably lower than the value of 2.0 which is considered an upper limit in
WebTAG, and suggest that the model is relatively inelastic in its response to journey time changes.
5.4.4 Sensitivity of Fuel Cost Elasticities
This section reports on the sensitivity of the fuel cost elasticities to changes in the model parameters. The table shows
how the elasticities reported for the home based work trip purpose vary in response to changes in the trip distribution
parameter.
Table 15 – Fuel Cost Elasticity Relative to Trip Distribution Parameter
Parameter Value AM Peak Inter Peak PM Peak 12 Hour 0.07 -0.14 -0.29 -0.16 -0.19
0.08 -0.16 -0.33 -0.18 -0.20
0.09 -0.18 -.037 -0.20 -0.22
0.10 -0.20 -0.41 -0.23 -0.25
0.11 -0.23 -0.45 -0.25 -0.27
Table 16 – Fuel Cost Elasticity Relative to Mode Choice Parameter
Parameter Value AM Peak Inter Peak PM Peak 12 Hour 0.50 -0.20 -0.41 -0.23 -0.25
0.60 -0.21 -0.45 -0.24 -0.26
0.70 -0.21 -0.50 -0.26 -0.28 0.80 -0.22 -0.55 -0.27 -0.29
Purpose Journey Time Elasticities 12 hour average
HBW -0.24
HBEB -0.40
HBO -0.28
NHBEB -0.42
NHBO -0.27
Overall -0.30
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6.1 Generalised Cost Formulation
The highway assignment procedure builds and loads paths through the network based on a behavioural generalised
cost formulation. This is a linear combination of time and distance of the following form:
Parameter values PPM and PPK have been derived from WebTAG Unit 3.5.6 – Values of Time and Operating Costs.
This ensures maximum compatibility between the assignment process and any economic assessments that are carried
out at a later stage. The value of time data taken from WebTAG was for the peak/inter-peak periods and had a base
year of 2002. The desired values were then factored to get the relevant year and peak hour. The PPK or Value of
Distance was calculated using the cost of fuel as well as the non-fuel vehicle operating costs. Again, this was factored
up to the relevant year and time period. The generalised cost parameters are determined by assessment year, time
period and user class as shown in Table 17 and Table 18 below.
Table 17 - Highway Assignment Generalised Cost Parameters – 2015
Parameter User Class 1 User Class 2 User Class 3 User Class 4
AM PPM 10.95 59.29 14.21 19.08
PPK 8.72 9.81 8.72 34.51
IP PPM 10.85 57.86 14.79 19.08
PPK 8.72 9.81 8.72 34.51
PM PPM 10.66 57.11 15.14 19.08
PPK 8.72 9.81 8.72 34.51
Table 18 - Highway Assignment Generalised Cost Parameters – 2030
Parameter User Class 1 User Class 2 User Class 3 User Class 4
AM PPM 11.73 64.65 15.23 20.45
PPK 8.41 9.55 8.41 35.33
IP PPM 11.63 63.09 15.85 20.45
PPK 8.41 9.55 8.41 35.33
PM PPM 11.43 62.27 16.23 20.45
PPK 8.41 9.55 8.41 35.33
6.2 Model Convergence
SATURN loops between assignment and simulation until steady flows are obtained, at which point the model is deemed
to have reached convergence. A high degree of convergence is important for two reasons:
- If the link flows and their corresponding flow-delay curves are not reasonably consistent then there is no reason to
believe that the modelled link flows and costs will be realistic; and
- It gives us confidence that, when the A1-SENSLR-MNB strategy is tested, any difference in flow between the
converged base and the test network can be attributed to the efforts of the scheme as opposed to random noise
which would arise from a base model which had not reached convergence.
In terms of convergence criteria, the DMRB recognises two types of measure, proximity indicators and stability
indicators.
6 Network Assignment Checks
and Characteristics
Cost = PPM * Time (in min) + PPK * Distance (in km)
Where: PPM = Pence Per Minute
PPK = Pence Per Kilometre
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Proximity indicators are those things which measure the degree to which the assignment sub-model has achieved its
stated aim. In the case of equilibrium assignments this means the degree to which Wardrop equilibrium has been
achieved. The DMRB recommends Delta as the proximity measure for Wardrop equilibrium assignments and states that
it must be less than 1%.
Stability indicators measure the similarity of the results of the previous and current iterations and it is these that are of
particular relevance in terms of the assignment-simulation loop. The DMRB recommends measures which look at
absolute changes in individual link flows and measures which look at the percentage change in total user costs across
the network as a whole.
Table 19 below summarises the recommended convergence criteria.
Table 19 - Summary of Convergence Criteria
Indicator Measure of Convergence Acceptable Value(s)
Proximity Indicators
Assignment ‘Delta’ Value Less than 1% (or at least stable with convergence fully documented and all other criteria met)
Assignment ‘Gap’ Value Less than 1%
Stability Indicators
Percentage of links with flow change (P) < 5% Four consecutive iterations greater than 90%
The Absolute Average Difference in flow per link (AAD)
Less than 1
The Relative Absolute Average Difference in flow per link (RAAD)
Less than 1%
Although proximity and stability usually accompany each other, they both should be assessed separately, as each
relates to different aspects of the iterative process. In terms of achieving stable and robust assignment results the
convergence criteria for the assignment delta value and one of the stability indicators should be met. However, all
convergence measures should be reported.
Table 20 to Table 23 summarises the convergence results for each modelled hour.
Table 20 - Summary of Convergence Statistics – 2015 Do Minimum
Convergence Measure Acceptable Value(s) Convergence Statistics
AM Peak Inter-Peak PM Peak
Assignment ‘Delta’ Value Less than 1% 0.0160 0.0009 0.0147
Assignment ‘Gap’ Value Less than 1% 0.022 0.00068 0.0086
Percentage of links with flow change (P) < 5%
Four consecutive iterations greater than 90%
98.7 100 99.2
The Absolute Average Difference in flow per link (AAD)
Less than 1 0.67 0.13 0.38
The Relative Absolute Average Difference in flow per link (RAAD)
Less than 1% 0.20 0.06 0.11
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Table 21 - Summary of Convergence Statistics – 2030 Do Minimum
Convergence Measure Acceptable Value(s) Convergence Statistics
AM Peak Inter-Peak PM Peak
Assignment ‘Delta’ Value Less than 1% 0.0448 0.0006 0.190
Assignment ‘Gap’ Value Less than 1% 0.020 0.0026 0.046
Percentage of links with flow change (P) < 5%
Four consecutive iterations greater than 90%
95.4 99.4 92.5
The Absolute Average Difference in flow per link (AAD)
Less than 1 1.66 0.31 2.5
The Relative Absolute Average Difference in flow per link (RAAD)
Less than 1% 0.47 0.12 0.68
Table 22 - Summary of Convergence Statistics – 2015 Preferred Scheme
Convergence Measure Acceptable Value(s) Convergence Statistics
AM Peak Inter-Peak PM Peak
Assignment ‘Delta’ Value Less than 1% 0.0061 0.0006 0.0083
Assignment ‘Gap’ Value Less than 1% 0.0025 0.00080 0.0086
Percentage of links with flow change (P) < 5%
Four consecutive iterations greater than 90%
99.2 99.4 99.9
The Absolute Average Difference in flow per link (AAD)
Less than 1 0.33 0.18 0.24
The Relative Absolute Average Difference in flow per link (RAAD)
Less than 1% 0.11 0.09 0.08
Table 23 - Summary of Convergence Statistics – 2030 Preferred Scheme
Convergence Measure Acceptable Value(s) Convergence Statistics
AM Peak Inter-Peak PM Peak
Assignment ‘Delta’ Value Less than 1% 0.0007 0.0001 0.009
Assignment ‘Gap’ Value Less than 1% 0.00039 0.00011 0.009
Percentage of links with flow change (P) < 5%
Four consecutive iterations greater than 90%
99.9 100 94.9
The Absolute Average Difference in flow per link (AAD)
Less than 1 0.08 0.03 1.97
The Relative Absolute Average Difference in flow per link (RAAD)
Less than 1% 0.03 0.01 0.60
As can be seen from Table 20 to Table 23 above, some of the stability indicators do not fall within the acceptable value.
However, it is outlined in the preceding paragraph that to achieve stable and robust assignment results, the convergence
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criteria for the assignment delta value and one of the stability indicators should be met. The results therefore meet these
criteria.
6.3 Network Wide Characteristics
In order to analyse the network wide impact of each scenario, statistics were extracted from the SATURN assignments
for each modelled time period and scenario. These include total travel distance, total travel time and average network
speed.
Results are summarised in Table 24 to Table 29 below and show that the introduction of the proposed bypass results in
a reduction in travel time and increased average vehicle speeds when compared to the Do-Minimum scenario.
However, an overall increase in vehicle kilometres is observed, primarily as a result of traffic from the south of Morpeth
using the bypass as opposed to travelling through the town centre which represents an increased journey length of
approximately 3km.
Table 24 - Network Statistics – 2015 AM Peak
Do-Minimum Preferred Scheme
Travel Distance (PCU km) 244553.5 244703.9
Travel Time (PCU hrs) 3656.6 3556.3
Network Speed (kph) 66.9 68.8
Table 25 - Network Statistics – 2030 AM Peak
Do-Minimum Preferred Scheme
Travel Distance (PCU km) 259261.6 260054.4
Travel Time (PCU hrs) 3924.7 3822.1
Network Speed (kph) 66.1 68
Table 26 - Network Statistics – 2015 Inter-Peak
Do-Minimum Preferred Scheme
Travel Distance (PCU km) 167858.5 167941
Travel Time (PCU hrs) 2313.5 2279.5
Network Speed (kph) 72.6 73.7
TAble 27 - Network Statistics – 2030 Inter Peak
Do-Minimum Preferred Scheme
Travel Distance (PCU km) 185868.6 186598.5
Travel Time (PCU hrs) 2584.4 2552.3
Network Speed (kph) 71.9 73.1
Table 28 - Network Statistics – 2015 PM Peak
Do-Minimum Preferred Scheme
Travel Distance (PCU km) 257115.5 258222.5
Travel Time (PCU hrs) 3895.4 3825.4
Network Speed (kph) 66 67.5
Table 29 - Network Statistics – 2030 PM Peak
Do-Minimum Preferred Scheme
Travel Distance (PCU km) 273734.4 274724.6
Travel Time (PCU hrs) 4205.7 4113.7
Network Speed (kph) 65.1 66.8
AECOM Morpeth Traffic Model Forecasting Report 25
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7.1 Introduction
This section details an analysis of the post-variable demand matrices and subsequent assigned network conditions in
the future year scenarios. This will include analysis of the traffic growth in comparison with national averages, details of
future year traffic flows on key links, a discussion of any significant incidents of junction delay and details of
volume/capacity on the various key links. The analysis will cover both future years and compare the Do Minimum and Do
Something networks.
Flow diagrams summarising the modelled outputs for key links in each scenario are contained in Appendix B.
7.2 Analysis of Matrix Totals
The matrix totals post-variable demand are summarised in Tables 30 and 31 on the following pages. Although UC4 is
included in the diagram, it is worth noting that this represents HGV traffic and as such was growthed using an NTM
factor as opposed to TEMPRO. The variable demand matrices have also been sectored to show how growth varies
within the model between the base year and modelled years. The results of this are displayed in Tables 32 to 37.
7 Analysis of Traffic Forecasts
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Table 30 - 2007 – 2015 Forecasting Process Matrix Totals
AM 2007 IP 2007 PM 2007
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin/Destination 10758 2714 7378 1181 Origin/Destination 1780 2654 5895 578 Origin/Destination 12059 3011 8748 950
AM 2015 TEMPRO + Developments IP 2015 TEMPRO + Developments PM 2015 TEMPRO + Developments
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin 11244 2916 7869 1227 Origin 1971 3066 7113 601 Origin 13563 3117 9908 987
Destination 12270 2802 8286 1227 Destination 1969 3043 7110 601 Destination 12805 3196 9534 987
AM 2015 Constrained to TEMPRO IP 2015 Constrained to TEMPRO PM 2015 Constrained to TEMPRO
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin 10789 2722 7400 1227 Origin 1886 2811 6244 601 Origin 12483 3117 9055 987
Destination 11129 2802 7633 1227 Destination 1880 2802 6224 601 Destination 12243 3057 8881 987
AM 2015 Balanced - Finished Pre-VaDMA IP 2015 Balanced - Finished Pre-VaDMA PM 2015 Balanced - Finished Pre-VaDMA
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin/Destination 10959 2765 7516 1227 Origin/Destination 1883 2807 6234 601 Origin/Destination 12363 3087 8968 987
AM 2015 Post-VADMA DM IP 2015 Post-VADMA DM PM 2015 Post-VADMA DM
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin/Destination 10959 2771 7671 1227 Origin/Destination 1904 2824 6397 600 Origin/Destination 12357 3085 9074 987
AM 2015 Post-VADMA DS IP 2015 Post-VADMA DS PM 2015 Post-VADMA DS
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin/Destination 10942 2803 7690 1227 Origin/Destination 1896 2847 6382 600 Origin/Destination 12400 3111 9092 987
AECOM Morpeth Traffic Model Forecasting Report 27
Capabilities on project:
Transportation
Table 31 - 2007 – 2030 Forecasting Process Matrix Totals
AM 2007 IP 2007 PM 2007
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin/Destination 10758 2714 7378 1181 Origin/Destination 1780 2654 5895 578 Origin/Destination 12059 3011 8748 950
AM 2030 TEMPRO + Developments IP 2030 TEMPRO + Developments PM 2030 TEMPRO + Developments
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin 11749 3014 8216 1465 Origin 2133 3326 7828 717 Origin 14140 3222 10459 1177
Destination 12697 2873 8647 1465 Destination 2114 3292 7831 717 Destination 13586 3331 9917 1177
AM 2030 Constrained to TEMPRO IP 2030 Constrained to TEMPRO PM 2030 Constrained to TEMPRO
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin 11056 2789 7583 1465 Origin 2026 3020 6707 717 Origin 12904 3222 9360 1177
Destination 11388 2873 7810 1465 Destination 2015 3004 6672 717 Destination 12690 3169 9205 1177
AM 2030 Balanced - Finished Pre-VaDMA IP 2030 Balanced - Finished Pre-VaDMA IP 2030 Balanced - Finished Pre-VaDMA
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin/Destination 11222 2831 7696 1465 Origin/Destination 2020 3012 6690 717 Origin/Destination 12797 3196 9283 1177
AM 2030 Post-VADMA DM IP 2030 Post-VADMA DM PM 2030 Post-VADMA DM
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin/Destination 11214 2839 7976 1465 Origin/Destination 2056 3040 7000 717 Origin/Destination 12803 3197 9491 1177
AM 2030 Post-VADMA DS IP 2030 Post-VADMA DS PM 2030 Post-VADMA DS
UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4
Origin/Destination 11213 2881 8027 1465 Origin/Destination 2051 3075 7007 717 Origin/Destination 12830 3234 9532 1177
AECOM Morpeth Traffic Model Forecasting Report 28
Capabilities on project:
Transportation
Table 32 - Sectored Growth
TEMPRO AM 2007-2015
Origin Destination
Northumberland 1.003 1.035
GB Average 1.056 1.056
AM Base 1 2 3 4 5 6
1 596 356 324 125 1220 55 2 555 413 363 456 225 313 3 218 112 787 488 432 468 4 111 245 441 1211 512 852 5 623 74 686 377 317 757 6 70 135 580 877 1669 4987
2015 AM DM
1 2 3 4 5 6
1 586 356 376 201 1231 92 2 556 390 396 459 210 335 3 319 111 930 512 433 473 4 322 237 428 1138 502 891 5 615 67 693 373 369 730 6 175 132 607 890 1568 4924
2015 AM DS
1 2 3 4 5 6
1 514 319 282 164 1090 70 2 497 339 368 422 185 283 3 274 85 853 471 390 455 4 319 210 373 999 380 759 5 541 53 582 299 330 644 6 155 95 541 782 1386 4348
2015 AM DM Growth
1 2 3 4 5 6
1 0.98 1.00 1.16 1.61 1.01 1.67 2 1.00 0.94 1.09 1.01 0.93 1.07 3 1.46 0.99 1.18 1.05 1.00 1.01 4 2.91 0.96 0.97 0.94 0.98 1.05 5 0.99 0.91 1.01 0.99 1.17 0.96 6 2.49 0.97 1.05 1.02 0.94 0.99
2015 AM DS Growth
1 2 3 4 5 6
1 0.86 0.90 0.87 1.31 0.89 1.26 2 0.90 0.82 1.01 0.93 0.82 0.90 3 1.26 0.76 1.08 0.97 0.90 0.97 4 2.88 0.86 0.85 0.82 0.74 0.89 5 0.87 0.71 0.85 0.79 1.04 0.85 6 2.21 0.70 0.93 0.89 0.83 0.87
AECOM Morpeth Traffic Model Forecasting Report 29
Capabilities on project:
Transportation
Table 33 - Sectored Growth
TEMPRO IP 2007-2015
Origin Destination
Northumberland 1.059 1.056
GB Average 1.084 1.084
IP Base 1 2 3 4 5 6
1 86 68 185 92 863 56 2 66 95 196 141 128 131 3 277 199 294 436 360 322 4 105 150 408 170 356 450 5 815 109 323 429 77 457 6 104 140 344 540 449 1482
2015 IP DM 1 2 3 4 5 6
1 80 63 291 118 856 68 2 63 88 203 148 129 145 3 412 207 438 468 380 377 4 125 166 443 173 383 532 5 772 100 338 426 90 444 6 114 150 394 616 430 1497
2015 IP DS 1 2 3 4 5 6
1 80 64 276 135 866 70 2 64 88 204 148 126 144 3 389 208 443 474 378 379 4 117 165 448 174 380 533 5 772 101 338 426 90 444 6 114 151 394 616 430 1497
2015 IP DM Growth
1 2 3 4 5 6
1 0.94 0.93 1.57 1.28 0.99 1.23 2 0.96 0.93 1.03 1.05 1.01 1.10 3 1.49 1.04 1.49 1.07 1.05 1.17 4 1.19 1.11 1.09 1.02 1.08 1.18 5 0.95 0.92 1.05 0.99 1.17 0.97 6 1.09 1.07 1.15 1.14 0.96 1.01
2015 IP DS Growth
1 2 3 4 5 6
1 0.94 0.93 1.49 1.46 1.00 1.26 2 0.97 0.93 1.04 1.04 0.99 1.10 3 1.40 1.05 1.50 1.09 1.05 1.18 4 1.11 1.10 1.10 1.02 1.07 1.18 5 0.95 0.92 1.04 0.99 1.16 0.97 6 1.09 1.07 1.15 1.14 0.96 1.01
AECOM Morpeth Traffic Model Forecasting Report 30
Capabilities on project:
Transportation
Table 34 - Sectored Growth
TEMPRO PM 2007-2015
Origin Destination
Northumberland 1.035 1.015
GB Average 1.061 1.061
PM Base 1 2 3 4 5 6
1 704 658 276 89 616 108 2 407 476 136 302 112 179 3 336 298 1020 438 465 558 4 82 477 548 1428 403 996 5 1193 205 479 457 380 2772 6 108 262 467 825 1222 5285
2015 PM DM
1 2 3 4 5 6
1 683 638 425 219 642 223 2 395 454 132 305 111 181 3 435 355 1166 461 482 597 4 142 500 606 1369 429 1035 5 1162 183 495 444 421 2621 6 126 263 470 888 1144 5300
2015 PM DS
1 2 3 4 5 6
1 684 639 413 229 653 223 2 401 454 134 305 107 181 3 383 351 1206 468 497 633 4 149 494 620 1381 425 1033 5 1162 183 495 445 421 2620 6 128 264 474 891 1144 5299
2015 PM DM Growth
1 2 3 4 5 6
1 0.97 0.97 1.54 2.45 1.04 2.07 2 0.97 0.95 0.97 1.01 0.99 1.01 3 1.30 1.19 1.14 1.05 1.04 1.07 4 1.74 1.05 1.11 0.96 1.07 1.04 5 0.97 0.89 1.03 0.97 1.11 0.95 6 1.17 1.01 1.01 1.08 0.94 1.00
2015 PM DS Growth
1 2 3 4 5 6
1 0.97 0.97 1.50 2.57 1.06 2.06 2 0.99 0.95 0.98 1.01 0.96 1.01 3 1.14 1.18 1.18 1.07 1.07 1.14 4 1.82 1.04 1.13 0.97 1.06 1.04 5 0.97 0.89 1.03 0.97 1.11 0.95 6 1.18 1.01 1.01 1.08 0.94 1.00
AECOM Morpeth Traffic Model Forecasting Report 31
Capabilities on project:
Transportation
Table 35 - Sectored Growth
AM Base 1 2 3 4 5 6
1 596 356 324 125 1220 55 2 555 413 363 456 225 313 3 218 112 787 488 432 468 4 111 245 441 1211 512 852 5 623 74 686 377 317 757 6 70 135 580 877 1669 4987
2030 AM DM
1 2 3 4 5 6
1 594 391 387 247 1293 117 2 581 434 428 494 235 388 3 342 120 922 515 430 486 4 329 290 441 1133 522 931 5 637 74 701 373 370 753 6 179 151 617 897 1605 5085
2030 AM DS
1 2 3 4 5 6
1 593 401 369 277 1301 121 2 590 433 431 489 231 387 3 340 121 945 520 441 510 4 376 285 436 1116 517 916 5 636 74 702 374 370 753 6 175 152 619 898 1604 5083
2030 AM DM Growth
1 2 3 4 5 6
1 1.00 1.10 1.20 1.97 1.06 2.11 2 1.05 1.05 1.18 1.08 1.04 1.24 3 1.56 1.07 1.17 1.06 1.00 1.04 4 2.97 1.18 1.00 0.94 1.02 1.09 5 1.02 1.00 1.02 0.99 1.17 0.99 6 2.55 1.12 1.07 1.02 0.96 1.02
2030 AM DS Growth
1 2 3 4 5 6
1 1.00 1.13 1.14 2.21 1.07 2.19 2 1.06 1.05 1.19 1.07 1.03 1.24 3 1.56 1.09 1.20 1.07 1.02 1.09 4 3.40 1.16 0.99 0.92 1.01 1.07 5 1.02 1.00 1.02 0.99 1.17 0.99 6 2.51 1.12 1.07 1.02 0.96 1.02
TEMPRO AM 2007-2030
Origin Destination
Northumberland 1.028 1.059
GB Average 1.159 1.159
AECOM Morpeth Traffic Model Forecasting Report 32
Capabilities on project:
Transportation
Table 36 - Sectored Growth
IP Base 1 2 3 4 5 6
1 86 68 185 92 863 56 2 66 95 196 141 128 131 3 277 199 294 436 360 322 4 105 150 408 170 356 450 5 815 109 323 429 77 457 6 104 140 344 540 449 1482
2030 IP DM 1 2 3 4 5 6
1 85 72 330 133 939 81 2 73 114 231 187 160 184 3 475 241 450 487 393 400 4 144 216 458 181 430 581 5 817 120 347 455 97 473 6 136 187 412 667 458 1601
2030 IP DS 1 2 3 4 5 6
1 85 72 315 154 951 83 2 74 114 234 187 159 184 3 457 243 456 494 397 405 4 144 216 463 181 428 581 5 818 120 347 455 97 473 6 137 187 413 667 458 1601
2030 IP DM
Growth 1 2 3 4 5 6
1 0.99 1.05 1.78 1.44 1.09 1.45 2 1.10 1.21 1.18 1.32 1.26 1.40 3 1.71 1.21 1.53 1.12 1.09 1.24 4 1.36 1.44 1.12 1.07 1.21 1.29 5 1.00 1.10 1.07 1.06 1.26 1.04 6 1.30 1.33 1.20 1.23 1.02 1.08
2030 IP DS
Growth 1 2 3 4 5 6
1 0.99 1.05 1.70 1.67 1.10 1.50 2 1.12 1.20 1.19 1.32 1.25 1.40 3 1.65 1.22 1.55 1.13 1.10 1.26 4 1.37 1.44 1.14 1.07 1.20 1.29 5 1.00 1.10 1.07 1.06 1.26 1.04 6 1.31 1.33 1.20 1.23 1.02 1.08
TEMPRO IP 2007-2015
Origin Destination
Northumberland 1.138 1.132
GB Average 1.227 1.227
AECOM Morpeth Traffic Model Forecasting Report 33
Capabilities on project:
Transportation
Table 37 - Sectored Growth
TEMPRO PM 2007-2015
Origin Destination
Northumberland 1.070 1.052
GB Average 1.17 1.17
PM Base 1 2 3 4 5 6
1 704 658 276 89 616 108 2 407 476 136 302 112 179 3 336 298 1020 438 465 558 4 82 477 548 1428 403 996 5 1193 205 479 457 380 2772 6 108 262 467 825 1222 5285
2030 PM DM
1 2 3 4 5 6
1 695 677 467 232 681 243 2 412 502 148 355 136 216 3 478 390 1158 467 489 624 4 203 540 619 1380 446 1064 5 1194 199 497 457 432 2695 6 150 300 490 922 1179 5532
2030 PM DS
1 2 3 4 5 6
1 695 678 453 249 686 247 2 418 502 149 354 134 217 3 425 385 1203 477 509 659 4 217 542 632 1385 443 1060 5 1194 199 497 457 432 2695 6 151 300 493 926 1179 5531
2030 PM DM Growth
1 2 3 4 5 6
1 0.99 1.03 1.69 2.60 1.10 2.25 2 1.01 1.06 1.08 1.18 1.21 1.21 3 1.42 1.31 1.14 1.07 1.05 1.12 4 2.47 1.13 1.13 0.97 1.11 1.07 5 1.00 0.97 1.04 1.00 1.13 0.97 6 1.39 1.15 1.05 1.12 0.97 1.05
2030 PM DS Growth
1 2 3 4 5 6
1 0.99 1.03 1.64 2.80 1.11 2.29 2 1.03 1.05 1.10 1.17 1.20 1.21 3 1.27 1.29 1.18 1.09 1.10 1.18 4 2.65 1.14 1.15 0.97 1.10 1.06 5 1.00 0.97 1.04 1.00 1.13 0.97 6 1.40 1.15 1.06 1.12 0.97 1.05
AECOM Morpeth Traffic Model Forecasting Report 34
Capabilities on project:
Transportation
Tables 32 to 37 on the preceding pages show how growth has varied across sector to sector movements for all peak
periods and modelled years; a comparison can also be made with the origin and destination factors extracted from
TEMPRO for both the local area and national average. What is notable from the results is that growth isn’t uniform
across all sector to sector movements as this will be dependent on the location of new developments. In some
instances there is also negative growth as zones within these sectors are affected when forecast traffic flows are
constrained back to TEMPRO.
The results show that there is significant growth in the sector 4 to sector 1 movement in the AM peak for both the 2015
and 2030 modelled years; this is reversed in the PM peak and is between sector 1 and sector 4. Analysis of the model
has shown that is as a result of a substantial development in the sector 1 area, Morpeth Fairmoor, which is generating a
lot of trips to and from the South East Northumberland area.
Overall, growth is generally greater than the local growth factor as this will be affected by the variable demand modelling.
Growth is however, much more comparable with the national average.
7.3 Analysis of Traffic Flow
The modelled traffic flows indicate that the addition of the A1-SENSLR-MNB to the network will attract vehicles away
from the town centre of Morpeth with a subsequent re-routing of vehicles to the A1 and the proposed bypass. Headline
statistics from the modelled scenarios can be summarised as follows:
- The introduction of the scheme results in increased traffic on the A1. For example, a 10.3% increase in 12 hour
AAWT flow is observed on the A1 northbound between Clifton and the new A1 junction, whilst a 12.2% increase is
observed southbound with the preferred scheme in place in 2030.
- The preferred scheme results in a significant reduction in volumes of traffic through the town centre of Morpeth. For
example:
o 2015 sees a 14.1% reduction northbound and a 8.7% reduction southbound in 12 hour AAWT flows on
the A192 Telford Bridge; a significant bottle neck in the town centre.
o Taking the A192 Peacock Gap, A197 Whorral Bank, A196 Dunces House, A192 Hepscott Park and A197
Clifton as a town centre cordon, the preferred scheme reduces 12 hour AAWT cordon flows by 16.2% in
2015 and 16.7% in 2030 (averaged for both directions).
o The A197 at Whorral experiences the greatest reduction in traffic across the network, with flow reductions
of 26% observed in 2030. This is primarily as a result of traffic diverting to the proposed A1-SENSLR-
MNB.
7.4 Analysis of Delay
The model results show that there are some junctions within the modelled area that experience very high junction delay
in the Do Minimum scenario. These junctions are predominantly, although not exclusively, within Morpeth town centre.
Analysis of the model in the Do Something scenario has shown that high junction delay is less of a problem as traffic
diverts away from Morpeth town centre to use the new A1 junction and the A1-SENSLR-MNB. The following section
summarises junctions with high delay for each of the peak periods for the future year 2030; this is considered to
represent a worst case scenario. For the purpose of this analysis, a value of 60 seconds was used to identify junctions
with high delay.
AECOM Morpeth Traffic Model Forecasting Report 35
Capabilities on project:
Transportation
Figure 3 – AM 2030 Do Minimum Delay
There are several junctions in the 2030 Do Minimum AM Peak which have a high level of delay; these are predominantly
in Morpeth town centre. It has already been outlined that there is a problem with congestion in Morpeth town centre and
the increase in traffic alongside no additional capacity only exacerbates this problem further. The delay ranges from 64-
227 seconds.
The A1 also experiences delay on the approach into Newcastle and this is reflective of conditions in the base year.
AECOM Morpeth Traffic Model Forecasting Report 36
Capabilities on project:
Transportation
Figure 4 – AM 2030 Do Something Delay
There is only one junction in Morpeth Town Centre which experiences a high level of delay in the 2030 Do Something
AM Peak. This is the Castle Bank/Goose Hill junction and is as a result of a reduction in traffic through this area as
people choose to use the bypass and the new A1 junction. Delay at this junction is 150 seconds which has reduced
from 202 seconds in the Do Minimum scenario.
Delay on the A1 approach into Newcastle is still present in the Do Something model as this is reflective of existing
conditions and will not be affected by the scheme.
AECOM Morpeth Traffic Model Forecasting Report 37
Capabilities on project:
Transportation
Figure 5 – IP 2030 Do Minimum Delay
Unlike the 2030 Do Minimum AM Peak, there are few junctions in the 2030 Do Minimum inter-peak which exhibit a high
level of delay. There is however, one exception.
A high level of delay is observed in the centre of Morpeth and is caused by right turning traffic on the minor road having
to give way to the mainline flow; the model shows 103 seconds of delay at this junction. This is considered
representative of the current situation.
AECOM Morpeth Traffic Model Forecasting Report 38
Capabilities on project:
Transportation
Figure 6 – IP 2030 Do Something Delay
The screen print above, taken from the 2030 IP Do Something SATURN model, illustrates that there are no junctions
which experience a high level of delay in this future year and time period.
AECOM Morpeth Traffic Model Forecasting Report 39
Capabilities on project:
Transportation
Figure 7 – PM 2030 Do Minimum Delay
In the 2030 Do Minimum PM Peak, there are several junctions which experience a high level of delay within the
modelled area. Similarly to the AM Peak, these junctions are, for the most part, in Morpeth town centre and are caused
by an increased level of traffic without any additional road capacity being provided. Delays range from 62-236 seconds.
Delay is also experienced on the A1 and A19 and is reflective of current conditions. Delay on the A697 is as a result of
the road approaching capacity.
AECOM Morpeth Traffic Model Forecasting Report 40
Capabilities on project:
Transportation
Figure 8 – PM 2030 Do Something Delay
Only one junction in Morpeth town centre exhibits a high level of delay in the 2030 Do Something PM Peak; Castle
Bank/Goose Hill junction. However, the delay at this junction is greatly reduced from the Do Minimum scenario. The
reduction in delay across the town centre is caused by a reduction in traffic flow as people choose to use the new A1
junction and bypass.
Delay is still experienced by vehicles using the A1, A19 and A697 as these links are unaffected by the scheme.
7.5 Analysis of Capacity
The model has been analysed to identify links that are at or above capacity in both the Do Minimum and Do Something
scenarios and ensure that this is reasonable. Similarly to the previous section, the problem is greatest in the Do
Minimum scenario with a number of links in Morpeth Town Centre being affected. This is analysed in greater detail in
the following section. For the purpose of this analysis a flow to capacity ratio of 85% was used to display links which are
at or above capacity.
AECOM Morpeth Traffic Model Forecasting Report 41
Capabilities on project:
Transportation
Figure 9 – AM 2030 Do Minimum Capacity
There are a number of links in the 2030 AM Do Minimum scenario which are at or above capacity. These are
predominantly links which are already recognised as being congested and therefore, as a result of an increase in traffic
flows, the problem is intensified.
Capacity issues on the northbound A192 approach to the Morpeth Fairmoor site access are as a result of development
traffic.
One link on the A1 is also approaching capacity at 91%. The A1 can become heavily congested in the AM peak and this
capacity issue is not considered unreasonable.
AECOM Morpeth Traffic Model Forecasting Report 42
Capabilities on project:
Transportation
Figure 10 – AM 2030 Do Something Capacity
In the 2030 Do Something AM Peak, the VoC for the eastbound approach and southbound approach to the Telford
Bridge remains a problem at 94% and 93% respectively. This however, is to a much lesser degree than in the Do
Minimum scenario when these links were operating above 100% capacity.
AECOM Morpeth Traffic Model Forecasting Report 43
Capabilities on project:
Transportation
Figure 11 – Inter-Peak 2030 Do Minimum Capacity
Similar to the AM peak, there are capacity issues at the Telford Bridge junction in the centre of Morpeth in the 2030
Inter-Peak model. This junction is recognised as being a highly constrained junction in the current year and it is
therefore not surprising that, without any highway improvements, this junction is exhibiting signs of congestion in the
future year 2030.
AECOM Morpeth Traffic Model Forecasting Report 44
Capabilities on project:
Transportation
Figure 12 – Inter-Peak 2030 Do Something Capacity
Figure 11 above shows that, with the inclusion of the A1-SENSLR-MNB, the capacity issues in the centre of Morpeth for
a standard inter-peak our disappear.
AECOM Morpeth Traffic Model Forecasting Report 45
Capabilities on project:
Transportation
Figure 13 – PM 2030 Do Minimum Capacity
There are several links in the centre of Morpeth where the volume to capacity ratio is above 85% in the 2030 PM peak.
Similarly to the AM Peak, these links have already been identified as suffering from congestion and therefore, as a result
of an increase in traffic flows without any additional road capacity, the problem is exacerbated.
AECOM Morpeth Traffic Model Forecasting Report 46
Capabilities on project:
Transportation
Figure 14 – PM 2030 Do Something Capacity
Similar to the AM peak, the Telford Bridge junction remains a problem in the 2030 PM peak with the inclusion of the A1-
SENSLR-MNB.
7.6 Analysis of Speeds
There are some areas of the model where very slow speeds are incurred by vehicles; these are mostly between origin
destination pairs within Morpeth Town Centre where the congestion problem is at its greatest. The problem is more
prevalent in the Do Minimum scenario as traffic diverts away from this area in the Do Something scenario. The following
section summarises some extreme examples of where very slow speeds are experienced in the 2030 model and the
reasons behind why these slow speeds have occurred. The 2030 model is considered to represent a worst case
scenario.
AM 2030 Do Minimum
926-931 (UC1)
Time (s) 408
Delay (s) 219
Dist (m) 490
Speed (kph) 4.32
AECOM Morpeth Traffic Model Forecasting Report 47
Capabilities on project:
Transportation
The average speed for this origin destination pair is low because vehicles experience a significant delay exiting from
zone 926 and giving way to traffic on the main flow. As the distance between the origin destination pair is small, vehicles
do not have time to increase their average speed.
The average speed for this origin destination pair is low because vehicles experience significant delay exiting the St
Mary’s Field/A197 junction and having to cross the main flow of traffic. As the distance between the origin destination
pair is small, vehicles do not have time to increase their average speed.
PM 2030 Do Minimum
AM 2030 Do Something
The average speed for this origin destination pair is low because it takes vehicles time to exit the St Mary’s Field/A197
junction. As the distance between the origin destination pair is small, vehicles do not have time to increase their average
speed.
PM 2030 Do Something
Similarly to the AM Peak, the average speed for this origin destination pair in the PM Peak is low because it takes
vehicles time to exit the St Mary’s Field/A197 junction. As the distance between the origin destination pair is small,
vehicles do not have time to increase their average speed.
7.7 Summary
The analysis has shown that there are some areas within the model that suffer from high delay, are over capacity or
have low speeds and is true of both the Do Minimum and Do Something scenarios. Investigation of these areas has
however shown that they are entirely reasonable and expected given the level of traffic in the model.
929-937 (UC1)
Time (s) 60
Delay (s) 26
Dist (m) 30
Speed (kph) 1.79
921-924 (UC1)
Time (s) 168
Delay (s) 160
Dist (m) 0
Speed (kph) 0
929-937 (UC1)
Time (s) 34
Delay (s) 9
Dist (m) 30
Speed (kph) 3.15
929-937 (UC1)
Time (s) 37
Delay (s) 8
Dist (m) 30
Speed (kph) 2.91
AECOM Morpeth Traffic Model Forecasting Report 48
Capabilities on project:
Transportation
Table 38 - Forecast Traffic Flows – AM Peak Period
Road Description Direction A Node B Node AM peak hour traffic flows (all traffic)
2015 DM 2015 DS % change 2030 DM 2030 DS % change
A1 North of A697 NB 211 209 666 679 1.84% 699 726 3.79%
SB 209 213 658 713 8.43% 715 765 7.07%
A1 A192 to A197 (Fairmoor) NB 111 115 786 935 18.94% 831 994 19.56%
SB 116 111 1402 1810 29.17% 1513 1917 26.69%
A1 Morpeth Bypass NB 108 107 786 906 15.30% 831 946 13.81%
SB 107 108 1402 1537 9.69% 1513 1674 10.64%
A1 South of A197 (Stannington) NB 144 143 1570 1615 2.86% 1621 1673 3.23%
SB 101 144 1997 2026 1.47% 2114 2169 2.60%
A192 Peacock Gap NB 138 173 748 363 -51.48% 760 402 -47.15%
SB 173 138 666 514 -22.80% 736 533 -27.60%
A193 Bridge Street EB 127 126 547 497 -9.13% 554 509 -8.14%
WB 126 127 630 428 -32.11% 636 434 -31.66%
A197 Whorral Bank EB 137 118 486 369 -23.97% 546 378 -30.84%
WB 118 137 916 686 -25.16% 919 727 -20.85%
A196 Dunce's House EB 119 708 357 352 -1.30% 360 363 0.80%
WB 708 119 444 303 -31.61% 501 319 -36.26%
A192 Hepscott Park EB 759 121 579 531 -8.17% 593 541 -8.75%
WB 121 759 412 417 1.13% 442 435 -1.58%
A192 Telford Bridge NB 158 126 1245 1008 -18.98% 1263 1024 -18.94%
SB 126 158 1161 1102 -5.05% 1164 1118 -3.97%
A197 Clifton EB 104 283 753 678 -9.98% 759 697 -8.21%
WB 283 104 545 440 -19.37% 551 446 -19.13%
A197 Pegswood Bypass EB 118 744 338 363 7.29% 392 420 7.17%
WB 744 118 533 686 28.62% 546 723 32.36%
MNB East of St George's
roundabout
EB 801 800 270 - 357 -
WB 800 801 481 - 520 -
MNB West of St George's
roundabout
EB 803 801 301 - 388 -
WB 801 803 509 - 551 -
AECOM Morpeth Traffic Model Forecasting Report 49
Capabilities on project:
Transportation
Table 39 - Forecast Traffic Flows – Inter Peak Period
Road Description Direction A Node B Node Interpeak hour traffic flows (all traffic)
2015 DM 2015 DS % change 2030 DM 2030 DS % change
A1 North of A697 NB 211 209 741 757 2.17% 799 829 3.72%
SB 209 213 700 741 5.83% 767 802 4.45%
A1 A192 to A197 (Fairmoor) NB 111 115 920 1231 33.75% 989 1341 35.52%
SB 116 111 938 1165 24.24% 1063 1274 19.80%
A1 Morpeth Bypass NB 108 107 920 995 8.05% 989 1072 8.41%
SB 107 108 938 1042 11.10% 1063 1187 11.61%
A1 South of A197 (Stannington) NB 144 143 1240 1261 1.73% 1320 1348 2.10%
SB 101 144 1342 1372 2.25% 1484 1517 2.22%
A192 Peacock Gap NB 138 173 534 421 -21.17% 619 507 -18.18%
SB 173 138 432 313 -27.49% 491 357 -27.32%
A193 Bridge Street EB 127 126 621 533 -14.19% 646 569 -11.85%
WB 126 127 532 462 -13.18% 554 491 -11.34%
A197 Whorral Bank EB 137 118 579 504 -13.02% 641 550 -14.29%
WB 118 137 551 493 -10.64% 595 528 -11.26%
A196 Dunce's House EB 119 708 287 277 -3.52% 303 298 -1.76%
WB 708 119 261 230 -11.53% 283 246 -13.21%
A192 Hepscott Park EB 759 121 432 412 -4.63% 462 437 -5.47%
WB 121 759 365 349 -4.32% 392 375 -4.44%
A192 Telford Bridge NB 158 126 907 794 -12.46% 966 840 -13.07%
SB 126 158 1048 939 -10.41% 1096 976 -10.93%
A197 Clifton EB 104 283 340 288 -15.45% 352 297 -15.62%
WB 283 104 426 352 -17.22% 443 354 -20.19%
A197 Pegswood Bypass EB 118 744 278 309 11.17% 305 336 10.46%
WB 744 118 311 339 8.98% 332 375 13.02%
MNB East of St George's roundabout EB 801 800 154 - 176 -
WB 800 801 142 - 179 -
MNB West of St George's
roundabout
EB 803 801 177 - 200 -
WB 801 803 163 - 204 -
AECOM Morpeth Traffic Model Forecasting Report 50
Capabilities on project:
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Table 40 - Forecast Traffic Flows – PM Peak Period
Road Description Direction A Node B Node PM peak hour traffic flows (all traffic)
2015 DM 2015 DS % change 2030 DM 2030 DS % change
A1 North of A697 NB 211 209 527 474 -10.09% 551 477 -13.54%
SB 209 213 1348 1480 9.81% 1416 1564 10.44%
A1 A192 to A197 (Fairmoor) NB 111 115 888 1055 18.85% 1018 1152 13.10%
SB 116 111 888 1098 23.72% 1018 1168 14.69%
A1 Morpeth Bypass NB 108 107 1348 1716 27.30% 1416 1808 27.68%
SB 107 108 281 344 22.39% 338 404 19.63%
A1 South of A197 (Stannington) NB 144 143 780 632 -18.99% 824 660 -19.90%
SB 101 144 409 370 -9.57% 435 397 -8.87%
A192 Peacock Gap NB 138 173 433 409 -5.73% 492 427 -13.09%
SB 173 138 604 530 -12.30% 562 536 -4.71%
A193 Bridge Street EB 127 126 1304 1150 -11.84% 1335 1183 -11.35%
WB 126 127 558 486 -12.94% 613 521 -15.01%
A197 Whorral Bank EB 137 118 534 446 -16.48% 602 449 -25.52%
WB 118 137 734 424 -42.23% 739 466 -36.94%
A196 Dunce's House EB 119 708 1952 1987 1.76% 1998 2074 3.85%
WB 708 119 1452 1556 7.15% 1608 1656 2.97%
A192 Hepscott Park EB 759 121 1211 1111 -8.21% 1223 1113 -9.05%
WB 121 759 764 613 -19.71% 882 668 -24.34%
A192 Telford Bridge NB 158 126 772 736 -4.62% 832 798 -4.01%
SB 126 158 579 614 6.09% 607 645 6.28%
A197 Clifton EB 104 283 566 475 -16.17% 541 478 -11.59%
WB 283 104 388 269 -30.75% 409 285 -30.13%
A197 Pegswood Bypass EB 118 744 415 561 35.15% 441 591 33.95%
WB 744 118 532 519 -2.43% 515 535 3.90%
MNB East of St George's roundabout EB 801 800 368 - 405 -
WB 800 801 188 - 263 -
MNB West of St George's
roundabout
EB 803 801 406 - 444 -
WB 801 803 219 - 300 -
AECOM Morpeth Traffic Model Forecasting Report 51
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8.1 Introduction
In order to test uncertainty in future year forecasting, it is recommended in WebTAG unit 3.15.5 that a series of
proportional sensitivity tests are conducted in order to account for the possibility of forecasting error in the central
scenario. To this end 2 additional future year scenarios have been developed. The preceding chapters of this report has
focused in detail on the central scenario, this section will deal with the construction and analysis of the Pessimistic and
Optimistic scenarios. A description of the 3 scenarios is detailed below:
- Pessimistic, with low growth and only near certain developments
- Central, with medium growth and more than likely/near certain developments
- Optimistic, with high growth and all developments
8.2 Background Growth
The background growth for the central scenario was calculated as described in Chapter 4.2, to adjust this into high and
low growth variations an additional step is required. This section details the calculation used to either increase or
decrease the central TEMPRO and NTM growth factors. The guidance in WebTAG unit 3.15.5 sets out the process for
taking such uncertainty into consideration in modelling a highway scheme.
‘To deal with such uncertainty in highway models, it is expected that the analyst will explore scenarios using an
appropriate range about the central forecast of ±2.5% for traffic forecasts one year ahead, rising with the square root of
the number of years to ±15% for forecasts 36 years ahead.’
Optimistic and pessimistic growth factors were therefore calculated using the following formulas;
Pessimistic factor = -2.5*
Optimistic factor = +2.5*
The results from these calculations are detailed in the following table for the Northumberland authority;
Table 41 - Pessimistic and Optimistic Growth Factors for the Castle Morpeth Authority
Forecast Year
Time Period
Trip End TEMPRO Pessimistic
Uncertainty Optimistic
Uncertainty
Pessimistic Factor Optimistic Factor
Orig. Dest. Orig. Dest. Orig. Dest
2015
AM 1.003 1.035 93% 107% 0.933 0.962 1.073 1.107
IP 1.059 1.056 93% 107% 0.985 0.982 1.133 1.13
PM 1.035 1.015 93% 107% 0.963 0.944 1.108 1.086
2030
AM 1.028 1.059 88% 112% 0.904 0.931 1.151 1.186
IP 1.138 1.132 88% 112% 1.001 0.996 1.274 1.268
PM 1.070 1.052 88% 112% 0.942 0.926 1.198 1.179
As can been seen in the above Table 41, the pessimistic scenario results in growth factors that are less than 1, meaning
that there is actually a decrease in traffic between the base and future years. This is due to the comparatively low level
of growth contained within TEMPRO for the Northumberland authority. Table 42 below shows a comparison between the
2007-2030 growth rates between Northumberland, a typical authority in North Yorkshire and the GB national average.
8 Sensitivity Testing
AECOM Morpeth Traffic Model Forecasting Report 52
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Table 42 – 2007-2030 Growth Rates
2007 to 2030
Northumberland North Yorkshire Great Britain
Orig Dest Orig Dest Orig Dest
AM 2.8% 5.9% 17.7% 19% 15.9% 15.9%
IP 13.8% 13.2% 24.3% 24.3% 22.7% 22.7%
PM 7% 5.2% 20% 19.1% 17% 17%
As Table 42 shows, in comparison to the Great Britain average and North Yorkshire growth factors, Castle Morpeth is
very low. Following the approved WebTAG method of accounting for uncertainty in TEMPRO growth we are left with
pessimistic matrices lower than the base year of 2007.
8.3 Uncertainty in Developments
As well as calculating low and high growth scenarios for the background growth we must also consider the status of the
planned developments within each of the three scenarios. To enable us to do this a planning status and uncertainty log
for each site was provided by the planning department at Northumberland County Council. The planning status comes
directly from the current status of each site within the planning department. This status was then used to assign each
site an uncertainty level from the below list (in increasingly levels of certainty) provided by WebTAG unit 3.15.5:
- Hypothetical
- Reasonably Foreseeable
- More than Likely
- Near Certain
The planning status of each development and subsequent uncertainty categorisation is listed in Table 43 below. The
tables also details within which of the scenarios each development is present.
Table 43 - Planned Developments in Modelled Area – Uncertainty Log
Site Proposed Land Use
Planning Status
Probability of Input (DfT Categories)
Future Year Scenarios
Likelihood of Site Completion %
OP CE PE
Hadston Industrial Estate
B2 Allocated site Reasonably foreseeable
OP 0 100
Morpeth Fairmoor (Northgate)
B1 Application awaiting a decision
More than likely OP CE 100 100
Morpeth Fairmoor (Northgate)
C3 Application awaiting a decision
More than likely OP CE 100 100
Longhorsely Land at East Road
C3 Application approved but not yet started
Near Certain OP CE PE 100 100
Morpeth Ex to Land Fairmoor
B1 Allocated site Reasonably foreseeable
OP 0 0
Morpeth Fairmoor Adj to A1
B1 Allocated site Reasonably foreseeable
OP 0 100
Morpeth Station Yard
B1 Site complete Near Certain OP CE PE 100 100
Stannington, part St. Mary's Hospital (mixed use)
C3 Application approved but not yet started
Near Certain OP CE PE 100 100
Stannington, part St. Mary's Hospital
B1 Application approved but
Near Certain OP CE PE 100 100
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Site Proposed Land Use
Planning Status
Probability of Input (DfT Categories)
Future Year Scenarios
Likelihood of Site Completion %
OP CE PE
(mixed use) not yet started
Ellington Colliery(mixed Use)
B1 Application awaiting a decision
More than likely OP CE 0 100
Ellington Colliery(mixed Use)
C3 Application awaiting a decision
More than likely OP CE 0 100
Lynemouth Colliery(mixed Use)
C3 Application awaiting a decision
More than likely OP CE 0 100
Lynemouth Colliery(mixed Use)
B1 Application awaiting a decision
More than likely OP CE 0 100
Low Stanners Morpeth mixed development
A1 Application awaiting a decision
More than likely OP CE 100 100
Goose Hill Factory site/ Davidsons Garage, Morpeth
A1 Application approved but not yet started
Near Certain OP CE PE 100 100
Goose Hill Factory site/ Davidsons Garage, Morpeth
C3 Application approved but not yet started
Near Certain OP CE PE 100 100
Stobswood Brickworks
C3 Application awaiting a decision
More than likely OP CE 0 100
St Georges,Morpeth Phase 1
C3
Planning application expired but working with HCA
More than likely OP CE 100 100
St Georges,Morpeth Phase 2
C3 Dependent on A1-SENSLR-MNB
Reasonably foreseeable
0 100
St Georges,Morpeth Phase 2
C3 Dependent on A1-SENSLR-MNB
Reasonably foreseeable
0 100
Hepscott Park B1 No planning status
Hypothetical OP 0 0
Hepscott Park C3 No planning status
Hypothetical OP 0 0
Park View, Hadston (Phase 3) West of A1068
C3 Application approved but not yet started
Near Certain OP CE PE 100 100
NCB Workshop site, Ashington
C3 Site under construction
Near Certain OP CE PE 100 100
ASDA, Lintonville Terrace, Ashington
A1 Site complete Near Certain OP CE PE 100 100
South of Wansbeck General Hospital, Ashington
C3 Site under construction
Near Certain OP CE PE 100 100
Ashwood Business B1 Site under Near Certain OP CE PE 100 100
AECOM Morpeth Traffic Model Forecasting Report 54
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Site Proposed Land Use
Planning Status
Probability of Input (DfT Categories)
Future Year Scenarios
Likelihood of Site Completion %
OP CE PE
Park, North Seaton construction
Wansbeck Business Park, Ashington
B1 Site under construction
Near Certain OP CE PE 100 100
Lintonville Enterprise Park, Ashington
B1 Site under construction
Near Certain OP CE PE 100 100
Former Ashington Hospital, Station Road
C3 Application approved but not yet started
Near Certain OP CE PE 0 100
Existing Northumberland College
C3 Application approved but not yet started
Near Certain OP CE PE 0 100
Ellington Colliery (site offices)
B1 Application approved but not yet started
Near Certain OP CE PE 100 100
Northumberland College (Hawthorne Annexe), Ashington
C3 Site under construction
Near Certain OP CE PE 100 100
South Loansdean, Morpeth (SHLAA-3007)
C3 SHLAA site Hypothetical OP 0 100
NCC sites Fire Station, County Hall adjoining land
C3 No planning status
Hypothetical OP 0 0
Stobhill South C3 SHLAA site Hypothetical OP 0 0
South Shore Links Road, Blyth
C3 Site under construction
Near Certain OP CE PE 100 100
Land at Wheatridge Park, Seaton Delaval
C3 Site under construction
Near Certain OP CE PE 100 100
Land at area 2A Chase Farm Drive, Blyth
C3 Site under construction
Near Certain OP CE PE 100 100
Land at West Blyth accessed from Chase Farm Drive, Blyth (Phases 1&2)
C3 Site under construction
Near Certain OP CE PE 50 100
Land at West Blyth accessed from Chase Farm Drive, Blyth (Phase 3)
C3 Application approved
Near Certain OP CE PE 0 100
Asda Stores Limited, Cowpen Road, Blyth
A1 Application approved
Near Certain OP CE PE 100 100
AECOM Morpeth Traffic Model Forecasting Report 55
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Site Proposed Land Use
Planning Status
Probability of Input (DfT Categories)
Future Year Scenarios
Likelihood of Site Completion %
OP CE PE
Tesco Supermarket, Market Place, Bedlington
A1 Application approved
Near Certain OP CE PE 100 100
Morrisons, Regent Street, Blyth
A1 Application approved
Near Certain OP CE PE 100 100
Narec Test Site, Albert Street, Blyth
B1 Application approved
Near Certain OP CE PE 100 100
Narec Test Site, Albert Street, Blyth
B1 Application approved
Near Certain OP CE PE 100 100
Queen Street, Amble
C3 Application approved
Near Certain OP CE PE 0 100
Queen Street, Amble
A1 Application approved
Near Certain OP CE PE 0 100
A1068 (land west of) and Marks Bridge (land south of), Amble
C3 Application approved
Near Certain OP CE PE 50 100
Coquet Enterprise Park, Amble
B2 Application approved
Near Certain OP CE PE 100 100
Land at Crofton Mill Industrial Estate, Blyth
C3 Application approved
Near Certain OP CE PE 100 100
Crossland Park, Cramlington
B1 Application approved
Near Certain OP CE PE 100 100
Amble Boat Co, Amble - Residential
C3 Application awaiting a decision
More than likely OP CE 0 100
Amble Boat Co, Amble - Employment
B1 Application awaiting a decision
More than likely OP CE 0 100
Amble Boat Co, Amble - Retail
A1 Application awaiting a decision
More than likely OP CE 0 100
Land East of A189 and South of Lanercost Park, Cramlington
C2 Application awaiting a decision
More than likely OP CE 100 100
West Hartford Business Park, Cramlington
B1 Application awaiting a decision
More than likely OP CE 25 50
South West Sector, Cramlington
C3 Growth point site
Reasonably foreseeable
OP 50 100
Sanderson Arcade, Morpeth
A1 Site completed Near Certain OP CE PE 100 100
The Kylins, Morpeth
C3 Site under construction
Near Certain OP CE PE 100 100
East Ashington SPD Area
B1 Allocated site Reasonably foreseeable
OP 0 100
AECOM Morpeth Traffic Model Forecasting Report 56
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Site Proposed Land Use
Planning Status
Probability of Input (DfT Categories)
Future Year Scenarios
Likelihood of Site Completion %
OP CE PE
East Ashington SPD Area
A1 Allocated site Reasonably foreseeable
OP 0 100
Jubilee Industrial Estate
B2 Allocated site Reasonably foreseeable
OP 0 100
North Seaton Industrial Estate
B2 Allocated site Reasonably foreseeable
OP 100 100
West Sleekburn Industrial Estate
B2 Allocated site Reasonably foreseeable
OP 100 100
Cambois C3 Growth point site
Reasonably foreseeable
OP 25 75
Welbeck Terrace, Pegswood
C3 Site under construction
Near Certain OP CE PE 100 100
The Mount, Morpeth
D1 Application approved
Near Certain OP CE PE 100 100
Land east of Whorral Bank Roundabout, Morpeth
D1 Application awaiting a decision
More than likely OP CE 100 100
Northgate Hospital (SHLAA 3079)
C3 Application submitted
More than likely OP CE 0 100
*This development is conditional on the completion of the bypass and as such, it has not been included in the future year matrices since
this will not enable a like for like comparison between the Do Minimum and Do Something scenarios.
8.4 Analysis of Matrices and Assignment
This section details the resulting Pessimistic and Optimistic matrices from the above process and gives a description of
the future year assigned network in each scenario. As with the central scenario the matrices were put through a variable
demand assessment to get the final matrix totals. Tables 44 and 45 below details a comparison of the post-variable
demand matrix totals for all three growth scenarios in the two forecast years:
Table 44 – 2015 Post-Variable Demand Sensitivity Totals
2015 – Variable Demand Totals
Time Period
Scenario Pre VADMA
DM Post VADMA
Pre-Post % Change
DS Post VADMA
Pre-Post % Change
DS-DM % Change
AM
Pessimistic 20981 21143 0.77% 21141 0.76% -0.01%
Central 22468 22628 0.71% 22662 0.86% 0.15%
Optimistic 23955 24076 0.51% 24129 0.73% 0.22%
IP
Pessimistic 10759 10913 1.43% 10889 1.20% -0.22%
Central 11524 11725 1.75% 11726 1.75% 0.00%
Optimistic 12289 12496 1.69% 12501 1.73% 0.04%
PM
Pessimistic 23695 23822 0.54% 23838 0.60% 0.07%
Central 25404 25502 0.39% 25590 0.73% 0.34%
Optimistic 27113 27182 0.25% 27291 0.65% 0.40%
AECOM Morpeth Traffic Model Forecasting Report 57
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Table 45 – 2030 Post-Variable Demand Sensitivity Totals
2030 – Variable Demand Totals
Time Period
Scenario Pre VADMA
DM Post VADMA
Pre-Post % Change
DS Post VADMA
Pre-Post % Change
DS-DM % Change
AM
Pessimistic 20604 20967 1.76% 20973 1.79% 0.03%
Central 23214 23494 1.21% 23586 1.60% 0.39%
Optimistic 25824 25916 0.36% 26096 1.05% 0.69%
IP
Pessimistic 11032 11387 3.22% 11374 3.10% -0.12%
Central 12439 12813 3.01% 12849 3.30% 0.28%
Optimistic 13845 14203 2.58% 14246 2.89% 0.30%
PM
Pessimistic 23419 23714 1.26% 23728 1.32% 0.06%
Central 26452 26668 0.81% 26774 1.22% 0.40%
Optimistic 29485 29591 0.36% 29763 0.94% 0.58%
As can been seen in the above tables the matrix totals follow a definite progression from Pessimistic to Central to
Optimistic in terms of the matrix size. The Pessimistic totals are still lower than the base year after the variable demand
process in the AM and PM time periods, despite there being a increase in the totals due to induced traffic. This stems
from the low growth present in TEMPRO for the Castle Morpeth region (as described in chapter 8.2) which results in a
very low Pessimistic matrix when all of the WebTAG guidance is followed to the letter.
Flow diagrams showing the forecast traffic on key links in included within Appendix B, as expected from the matrix
totals this shows an increase in traffic both along the bypass and through the town centre in Optimistic scenario. The
Pessimistic scenario, following on from the issues described above has a level of traffic lower than that of the 2007 base
in some areas and as such is relatively free flowing.
AECOM Morpeth Traffic Model Forecasting Report 58
Capabilities on project:
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9.1 Introduction
In order to best represent the value for money scheme of the A1-SENSLR-MNB, a number of additional models have
been created as summarised in this section of the report.
9.2 Unconstrained Models
The TEMPRO growth factors for Northumberland and Castle Morpeth are extremely low in comparison to similar
geographical areas and the Great Britain average. They are based on demographic forecasts that do not match the
Council’s vision for Morpeth and South East Northumberland once the A1-SENSLR-MNB has been completed. An
analysis of the planning data which underpins the TEMRPO growth factors has therefore been undertaken for the Castle
Morpeth area to show where any discrepancies may lie.
9.2.1 Employment - the planning data predicts almost no growth in jobs across Northumberland as a whole between 2010
and 2020 and a marginal decrease in jobs for Castle Morpeth. This contradicts the Economic Impact Report which
suggests that the completion of the bypass has the potential to trigger the development of around 5,000 jobs across
South East Northumberland. Additionally, a recent report prepared by David Lock Associates et al has identified that all
five "realistic" development scenarios for Morpeth generate between 1,700 and 3,000 jobs in Morpeth itself. This is
based on a job generation methodology produced on behalf of English Partnerships. The in TEMPRO is also
contradictory to the North East Economic Model which suggests an overall growth in the number of full time equivalent
jobs in Northumberland up between 2010 and 2030 of 2.56%; this figure is expected to be higher in Morpeth.
9.2.2 Households - the planning data predicts growth in households of 6-7% between 2010 and 2020 for Northumberland and
Castle Morpeth which is less than the predictions for, say Durham (9%) and Newcastle (10%). For planning purposes
the County Council still uses RSS housing figures for the County although, going forward, national planning policy is that
we should be seeking to increase provision above RSS levels. Housing provision will be addressed through the new
authority LDF Core Strategy but this is at a relatively early stage in plan preparation.
9.2.3 Population – the planning data suggests a significant reduction in working age population in Northumberland and a
major increase in the 65+ age group. Data comes from the ONS population projections to 2033 with the calculations
mainly being based on the last 5 years worth of historical data alongside 'expert advice' on future trends. Looking at the
data there is an increase in 65+ between 2003 and 2008 but it is difficult to see how this can be projected forward to
2033. The same applies to the predicted downturn in working age population (15-65). The delivery of the SENSLR is
about removing barriers to development and creating more sustainable communities through additional residential
provision and employment growth. This should change established demographics.
When the forecasted trip generation for each of the development sites is calculated for the Castle Morpeth area, the
percentage growth is significantly higher than the TEMPRO growth factor. This is highlighted in Tables 46 and 47
below.
Table 46: 2007-2015 TEMPRO/Development growth comparison (Castle Morpeth)
Time Period Base * TEMPRO 6.2 Base + Developments
AM average growth 1.55% 19.48%
Interpeak average growth 4.88% 23.68%
PM average growth 2.11% 19.27%
9 Additional Testing
AECOM Morpeth Traffic Model Forecasting Report 59
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Table 47: 2007-2030 TEMPRO/Development growth comparison (Castle Morpeth)
Time Period Base * TEMPRO 6.2 Base + Developments
AM average growth 1.80% 22.73%
Interpeak average
growth 8.62% 27.08%
PM average growth 3.14% 22.33%
By constraining back to TEMPRO, the traffic conditions in the future years are being significantly underestimated. An
alternative methodology has therefore been developed and a full economic assessment for this carried out.
9.2.4 Methodology
In order to provide a more realistic representation of the forecast traffic growth in the Castle Morpeth area, traffic growth
in this area has not been constrained back to TEMPRO. Where developments have been specified, the development
traffic has been added to the base row and column total for this zone but has not be growthed by TEMPRO. Where no
developments are specified, the base row and column totals has been growthed to the future level using TEMPRO
growth factors to take account of background traffic growth.
In the wider modelled area, where zones represent greater spatial areas and the impact of development trips on traffic
levels in Castle Morpeth is less pronounced, the methodology outlined in WebTAG guidance has been adopted and all
zones in this area are constrained back to TEMPRO.
The new methodology is summarised in the Table 48 below.
Table 48: Proposed Methodology for Forecasting
Zone Methodology
Castle Morpeth zone – no
development
Base * Castle Morpeth TEMPRO
Castle Morpeth zone – with
development
Base + Development, no TEMPRO
Wider modelled area zone
– no development
Base * Northumberland TEMPRO, constrained back to wider
modelled area TEMPRO total
Wider modelled area zone
– with development
Base * Northumberland TEMPRO + Development, constrained back
to wider modelled area TEMPRO total
A full economic assessment has been carried out using the above methodology and is summarised in the A1-SENSLR-
MNB Economic Assessment Report.
9.3 Off-peak, Weekend and Bank Holiday Models
The Department for Transport have suggested that all economic assessment should be undertaken for a full year of
8760 hours. This would take account of not only AM, PM and inter-peak hours, but also of off-peak, weekend and bank
holiday traffic. In order to provide appropriate time, distance and demand skims for the economic assessment new
traffic models needed to be created to represent traffic conditions during these time periods. The methodology adopted
to undertake this process is summarised below.
AECOM Morpeth Traffic Model Forecasting Report 60
Capabilities on project:
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The TUBA methodology guidance states that in order to extend the annualisation to an hour which has not been
specifically modelled in the original scope of the scheme, it is preferable to use appropriate 24 hour traffic counts to
factor a demand matrix as opposed to actual TUBA cost data (e.g. journey time), as the relationship may not be linear.
Therefore, in order to account for all off-peak, weekend and bank holiday hours the demand matrices in the current
model have been factored by appropriate traffic counts and reassigned to the SATURN model to produce new journey
time costs. The inter-peak ‘other’ matrix and inter-peak HGV matrix have been used as a starting point for this analysis
as this time period best represents the journey purposes which would be observed.
The following section sets out the methodology in more detail using the off-peak time period as an example.
9.3.1 Methodology
The ‘other’ journey purpose demand matrix for the inter-peak model has been factored to the level of the average off-
peak hour. In order to adjust the inter-peak matrix to the off-peak level, the following factor has been used:
Factor = Average Off-Peak Hour / Average Inter-Peak Hour
As the demand matrix for the ‘other’ journey purpose is being used as the basis for the off-peak traffic, it was also
necessary to calculate the percentage of ‘other’ traffic which makes up the full demand matrix. An analysis of the light
vehicle matrix totals for all of the modelled years was therefore carried out.
The ‘other’ matrix needed to be factored up to represent a full inter-peak demand matrix and then factored down to
represent the off-peak period. This has been calculated as follows:
(1 / Percentage of ‘Other’ Traffic) * Inter-Peak to Off-Peak Factor
It was also necessary to take into account the HGV traffic and the proportion of the total traffic which is assigned to
HGVs. As the model includes a section of the A1, there will be a number of long haul HGV journeys present in the off-
peak period. There was no classified data available for the overnight time period and so the same calculation was used
for the inter-peak HGV demand matrix. It is logical to assume that the HGV traffic would not decrease to the same
amount as the light traffic due to the A1 overnight being a major route for goods vehicles. However, there is currently no
information to back this assumption up and so decreasing it by the same level can be considered a more robust
approach.
Once the matrices were formulated for all the required years and scenarios, they were assigned to the SATURN
networks and results extracted in the usual manner. The results from this SATURN run were then adapted into the
TUBA in the same way as the other time periods.
The flow chart in Figure 15 overleaf, shows the whole process from start to finish
The same methodology was adopted for weekend and bank holiday hours using appropriate ATC data. This is
summarised below.
Weekend and bank holiday annualisation was calculated as follows:
- Hours which were within 90% of an average weekday inter-peak hour were determined and flow weighted to
calculate the annualisation factor for the TUBA assessment. Within the TUBA assessment, the same journey
time/distance cost results from the inter-peak ‘other’ model and the demand matrix for the inter-peak ‘other’ journey
purpose were used and factored up to the full hourly demand;
- The average hourly flow for al other hours was calculated;
- A factor for reducing the inter-peak ‘other’ matrix to weekend or bank holiday levels was calculated;
- The ‘other’ demand matrix was increased to a full hour and then factored to an average weekend or bank holiday
hour;
- The inter-peak HGV matrix was factored down to reduce it to weekend or bank holiday levels;
- The matrices were assigned to the SATURN model and the outputs extracted in the usual manner.
AECOM Morpeth Traffic Model Forecasting Report 61
Capabilities on project:
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The following factors were used for reducing a full inter-peak ‘other’ matrix and an inter-peak HGV matrix to off-peak,
weekend and bank holiday levels.
Table 49: Off-Peak, Weekend and Bank Holiday Factors
Time Period Factor
Off-Peak Factor 0.193
Weekend Factor 0.329
Bank Holiday Factor 0.368
AECOM Morpeth Traffic Model Forecasting Report 62
Capabilities on project:
Transportation
Figure 15: Off-Peak, Weekend and Bank Holiday Forecasting Methodology
Extract the relevant model outputs and include in the
TUBA assessment
Run the matrices through current SATURN networks
setup for only 2 user classes
Stack the two matrices into a single off-peak
demand matrix
Factor the matrix to first increase it to the full
interpeak demand and then reduce it to off-peak
levels
Factor the matrix to reduce it to off-peak
levels
Extract the ‘HGV’ journey purpose demand matrix
Extract the ‘Other’ journey purpose demand matrix
2015 and 2030 DM inter-peak demand
matrices
AECOM Morpeth Traffic Model Forecasting Report 63
Capabilities on project:
Transportation
10.1 Summary
This report describes the methodology and assumptions that have underpinned the development of the future year
models that have produced the traffic forecasts used in the design, economic and environmental assessment of the of
the A1-South East Northumberland Strategic Link Road-Morpeth Northern Bypass (A1-SENSLR-MNB)
The production of the Base Year model is detailed in the Local Model Validation Report and this formed the basis for the
production of the forecast models.
There are no committed highway schemes of significance in the area therefore the Do-Minimum highway network was
assumed to be the same as the base situation in the future year scenarios.
The preferred option consists of the construction of a new bypass route between the A1 and the existing Pegswood
Bypass, with the construction of a new roundabout on the A1 at St Leonards.
Future year demand matrices were produced for the proposed opening year of 2015 and design year of 2030 based
upon growth predicted by the National Trip End Model (NTEM). Account was also taken of proposed local employment
and residential developments specifically with the total growth factors adjusted accordingly to keep them in line with
NTEM.
To take account of the impacts of future year traffic conditions a full variable demand modelling (VDM) approach has
been taken in developing the future year matrices. A freestanding variable demand modelling process has been
developed for the Morpeth model which is fully compliant with the Department for Transport’s variable demand
guidelines. The process used for the Morpeth project has been based on a similar model developed previously by
AECOM and approved by the Department for Transport.
The introduction of the proposed bypass results in a reduction in travel time and increased average vehicle speeds when
compared to the Do-Minimum scenario. However, an overall increase in vehicle kilometres is observed, primarily as a
result of traffic from the south of Morpeth using the bypass as opposed to travelling through the town centre which
represents an increased journey length of approximately 3km.
The modelled traffic flows indicate that the addition of the A1-SENSLR-MNB to the network will attract vehicles away
from the town of Morpeth with a subsequent re-routing of vehicles to the A1 and the proposed bypass.
10 Summary
Appendices
Appendix A – Scheme
Appendix B – Traffic Flow Diagrams
A1
256 N
127 1
150
23
A197
515 2
55 A192
117 13117 13
17 4 206
Mitford Rd A192 140 20 11 12 21 59 N
53 9 0 184
151 9 28 18
Coopies Lane 197 6 1 A192 231 19
53 27 A196 44 A197 559
193 11 312 83 22
15 288 11 202
274 28 33 37
52 81 407 14 341 225
99 21 61 298 78 25 20
20 10 122 101
30 114 264 172
13 19 80 16
352 6 16352 6 16
80 399
226 56 520
3 48 216 286 15 100 142 684 18
52 5 71 37 409 120
246 128 17 45 345
16 21 A192 48
4 223 A192 297
33 23 59
204 297
15 47 372 278 25
365 84 52
92
24 319 614 212 27
A1 23 103 31 197
A197 A196 53
114 26 193
29 51 15
Key Trip Purpose 76 274
1 52
Commute 198 99 28
Business 27 20
Other 76
HGV 18 A192
30
Client: Northumberland County CouncilAM 2015 Do Minimum Constrained Model Flows
A1
143 53
187 73 1 32 N
95 1
128
19
367 56 A197
176 2 57 1 31
52 A192
121 9121 9
8 5 132
Mitford Rd A192 148 32 11 12 21 28 N
42 11 2 174
149 9 6 18
Coopies Lane 206 6 1 A192 230 19
42 27 A196 44 A197 365
192 11 305 56 22
15 154 11 182
127 28 29 41
47 80 228 14 340 214
74 21 58 248 63 30 20
20 10 93 90
22 97 222 173
13 19 70 16
329 6 16
73 228
185 50 484
3 46 161 257 15 92 115 510 18
23 5 65 29 400 109
214 128 17 51 311
20 15 A192 39
4 218 A192 277
34 23 52
211 257
15 45 390 293 25
314 81 52
66
24 294 461 217 27
A1 28 98 25 206A1
A197 A196 42
125 26 192
29 54 15
Key TripPurpose 77 127
1 47
Commute 223 74 28
Business 34 20
Other 75
HGV 24 A192
30
Client: Northumberland County CouncilAM 2015 Do Something Constrained Model Flows
A1
322 N
128 1
184
27
A197
503 2
58 A192
140 13140 13
20 4 252
Mitford Rd A192 141 20 11 12 21 57 N
54 13 0 192
151 9 54 22
Coopies Lane 197 7 1 A192 230 19
54 27 A196 43 A197 532
191 11 308 84 22
25 327 14 209
294 28 39 47
55 85 401 14 314 224
103 25 66 312 81 33 20
24 10 153 98
36 117 276 166
13 23 75 19
351 6 16351 6 16
82 388
226 59 507
3 50 210 274 15 99 140 671 18
51 5 74 45 403 125
245 131 17 57 353
22 32 A192 57
4 246 A192 298
36 23 60
207 299
17 50 366 276 25
362 84 54
91
24 316 605 218 27
A1 31 107 37 197
A197 A196 54
115 26 191
29 52 25
Key Trip Purpose 78 294
2 55
Commute 212 103 28
Business 31 24
Other 79
HGV 22 A192
30
Client: Northumberland County CouncilAM 2030 Do Minimum Constrained Model Flows
A1
191 88
194 76 1 32 N
96 1
134
23
384 72 A197
181 2 62 1 31
54 A192
154 9154 9
9 5 141
Mitford Rd A192 142 32 11 12 21 23 N
49 12 2 171
158 9 5 21
Coopies Lane 196 7 1 A192 229 19
49 27 A196 39 A197 384
198 11 308 58 22
18 153 13 186
130 28 32 49
49 85 227 14 341 213
82 25 60 254 59 36 20
24 10 112 95
26 104 228 173
13 23 70 19
328 6 16
74 224
185 46 485
3 54 162 256 15 95 114 507 18
23 5 68 35 397 107
212 131 17 60 315
24 18 A192 47
4 225 A192 278
36 23 53
217 260
18 53 394 295 25
315 82 62
67
24 290 462 218 27
A1 34 96 30 196A1
A197 A196 49
139 26 198
29 56 18
Key TripPurpose 79 130
1 49
Commute 227 82 28
Business 37 24
Other 80
HGV 29 A192
30
Client: Northumberland County CouncilAM 2030 Do Something Constrained Model Flows
A1
39 N
140 1
190
16
A197
58 2
142 A192
300 13300 13
11 12 104
Mitford Rd A192 41 5 18 12 21 116 N
59 5 0 314
149 9 10 23
Coopies Lane 43 19 0 A192 92 19
79 27 A196 90 A197 104
142 11 388 105 22
16 41 19 303
39 28 59 20
109 128 51 14 101 338
119 16 108 55 90 15 20
11 10 170 110
10 163 102 296
13 19 174 24
54 6 1654 6 16
76 89
186 156 163
3 12 66 62 15 259 230 133 18
90 5 92 13 570 206
235 245 17 43 497
18 22 A192 35
4 59 A192 80
77 23 113
196 268
14 21 114 370 25
96 175 37
137
24 346 96 366 27
A1 27 171 35 43
A197 A196 79
15 26 142
29 45 16
Key Trip Purpose 52 39
6 109
Commute 13 119 28
Business 37 11
Other 50
HGV 1 A192
30
Client: Northumberland County CouncilIP 2015 Do Minimum Constrained Model Flows
A1
27 56
30 71 0 32 N
98 1
171
9
24 61 A197
32 2 55 0 31
142 A192
250 9250 9
7 12 90
Mitford Rd A192 40 5 15 12 21 78 N
54 6 1 291
149 9 9 22
Coopies Lane 41 17 1 A192 86 19
73 27 A196 82 A197 94
142 11 361 86 22
15 33 19 274
32 28 51 19
60 116 28 14 97 332
106 16 92 41 82 15 20
11 10 132 77
7 128 91 263
13 13 142 18
42 6 16
66 71
156 143 142
3 12 48 56 15 226 189 105 18
70 5 88 11 534 183
203 238 17 37 441
15 21 A192 33
4 59 A192 68
67 23 102
195 236
12 21 113 365 25
78 156 33
116
24 316 83 342 27
A1 24 159 32 41A1
A197 A196 73
16 26 142
29 57 15
Key TripPurpose 55 32
8 60
Commute 19 106 28
Business 41 11
Other 57
HGV 3 A192
30
Client: Northumberland County CouncilIP 2015 Do Something Constrained Model Flows
A1
45 N
148 1
230
16
A197
62 2
154 A192
365 13365 13
14 13 113
Mitford Rd A192 44 5 20 12 21 125 N
64 6 0 349
151 9 11 27
Coopies Lane 43 22 0 A192 98 19
84 27 A196 96 A197 110
142 11 413 113 22
19 45 22 325
42 28 64 23
124 136 56 14 100 346
126 19 115 67 95 18 20
14 10 205 116
13 189 108 304
13 20 182 26
57 6 1657 6 16
80 89
187 165 172
3 14 71 69 15 267 241 142 18
92 5 99 16 586 220
242 255 17 48 519
19 27 A192 43
4 64 A192 85
84 23 119
207 275
16 26 120 380 25
101 187 43
141
24 358 103 385 27
A1 30 183 41 43
A197 A196 84
18 26 142
29 48 19
Key Trip Purpose 56 42
9 124
Commute 15 126 28
Business 40 14
Other 56
HGV 1 A192
30
Client: Northumberland County CouncilIP 2030 Do Minimum Constrained Model Flows
A1
31 68
33 76 1 32 N
105 1
203
11
29 84 A197
36 2 64 1 31
151 A192
325 10325 10
9 13 96
Mitford Rd A192 43 5 17 12 21 84 N
59 7 1 316
155 9 8 27
Coopies Lane 45 20 2 A192 92 19
79 27 A196 88 A197 100
146 11 387 92 22
18 35 23 291
34 28 55 23
117 119 31 14 102 329
109 19 97 45 86 18 20
13 10 161 84
9 146 99 273
13 15 153 22
44 6 16
69 77
155 152 153
3 14 51 60 15 235 202 112 18
75 5 94 14 534 194
193 245 17 44 455
17 25 A192 39
4 64 A192 73
72 23 108
203 243
15 25 121 377 25
83 166 41
124
24 311 89 354 27
A1 28 169 39 45A1
A197 A196 79
17 26 146
29 62 18
Key TripPurpose 63 34
9 117
Commute 21 109 28
Business 45 13
Other 67
HGV 3 A192
30
Client: Northumberland County CouncilIP 2030 Do Something Constrained Model Flows
A1
495 N
33 1
202
7
A197
311 2
126 A192
177 15177 15
7 8 452
Mitford Rd A192 283 18 12 12 21 68 N
19 6 0 236
69 9 14 12
Coopies Lane 224 8 2 A192 326 19
35 27 A196 69 A197 204
79 11 267 56 22
9 123 9 255
236 28 68 10
61 204 388 14 279 366
201 7 118 459 67 11 20
10 10 227 26
13 102 488 78
13 3 33 3
221 6 16221 6 16
60 233
278 89 740
3 4 262 191 15 219 101 543 18
55 5 55 9 339 164
191 227 17 15 557
9 9 A192 20
4 305 A192 494
69 23 121
120 300
7 11 656 229 25
365 87 17
60
24 216 368 383 27
A1 8 92 16 224
A197 A196 35
112 26 79
29 32 9
Key Trip Purpose 134 236
15 61
Commute 86 201 28
Business 28 10
Other 47
HGV 2 A192
30
Client: Northumberland County CouncilPM 2015 Do Minimum Constrained Model Flows
A1
259 68
228 39 1 32 N
30 1
198
5
81 55 A197
210 2 52 0 31
119 A192
159 15159 15
5 9 370
Mitford Rd A192 156 21 6 12 21 44 N
23 6 0 194
72 9 15 12
Coopies Lane 96 9 2 A192 319 19
41 27 A196 53 A197 162
84 11 264 36 22
9 114 9 229
183 28 54 10
49 188 286 14 249 309
183 7 98 257 48 10 20
9 10 153 38
11 93 354 120
13 3 51 3
163 6 16
50 203
255 71 628
3 4 258 187 15 197 109 473 18
49 5 47 8 342 128
148 216 17 16 511
9 8 A192 19
4 277 A192 434
66 23 106
133 277
7 11 519 257 25
381 99 17
64
24 183 356 358 27
A1 9 80 14 96A1
A197 A196 41
171 26 84
29 34 9
Key TripPurpose 126 183
14 49
Commute 85 183 28
Business 30 9
Other 50
HGV 3 A192
30
Client: Northumberland County CouncilPM 2015 Do Something Constrained Model Flows
A1
456 N
34 1
253
8
A197
413 2
131 A192
191 16191 16
8 8 477
Mitford Rd A192 297 22 14 12 21 68 N
21 7 0 251
71 9 15 14
Coopies Lane 229 10 2 A192 320 19
37 27 A196 71 A197 260
82 11 266 57 22
11 130 11 262
238 28 71 12
63 217 433 14 280 383
210 9 121 409 55 13 20
12 10 235 39
15 119 430 88
13 3 38 3
215 6 16215 6 16
53 273
266 88 714
3 3 262 225 15 230 101 568 18
60 5 65 11 371 165
208 238 17 19 554
11 11 A192 24
4 271 A192 483
72 23 112
131 284
8 12 631 243 25
360 83 20
58
24 235 404 399 27
A1 10 95 19 229
A197 A196 37
170 26 82
29 44 11
Key Trip Purpose 140 238
19 63
Commute 88 210 28
Business 29 12
Other 50
HGV 4 A192
30
Client: Northumberland County CouncilPM 2030 Do Minimum Constrained Model Flows
A1
273 89
227 41 1 32 N
32 1
240
6
144 64 A197
247 2 54 0 31
125 A192
173 15173 15
6 10 387
Mitford Rd A192 165 20 6 12 21 45 N
25 6 1 199
75 9 15 14
Coopies Lane 97 10 2 A192 326 19
42 27 A196 55 A197 159
85 11 268 37 22
11 120 11 230
207 28 56 12
51 203 309 14 243 334
195 8 101 254 49 13 20
11 10 158 40
13 95 353 122
13 3 54 3
168 6 16
52 222
250 73 613
3 4 249 197 15 207 112 495 18
48 5 48 9 349 133
158 221 17 19 511
11 9 A192 23
4 279 A192 447
71 23 110
140 273
8 13 515 263 25
374 103 20
63
24 193 368 370 27
A1 11 81 17 97A1
A197 A196 42
183 26 85
29 36 11
Key TripPurpose 131 207
17 51
Commute 96 195 28
Business 33 11
Other 53
HGV 5 A192
30
Client: Northumberland County CouncilPM 2030 Do Something Constrained Model Flows
A1
273 N
132 1
161
23
A197
511 2
58 A192
124 13124 13
16 5 222
Mitford Rd A192 147 22 12 12 21 65 N
54 9 0 204
160 9 30 18
Coopies Lane 207 6 1 A192 244 19
52 27 A196 42 A197 556
205 11 314 83 22
22 315 11 210
297 28 34 35
54 85 416 14 335 238
109 21 68 314 82 24 20
20 10 160 99
30 119 268 174
13 19 76 15
373 6 16373 6 16
80 397
236 56 515
3 40 222 287 15 105 141 699 18
53 5 71 38 426 122
259 136 17 42 366
14 28 A192 48
4 232 A192 315
36 23 60
214 313
15 40 371 294 25
379 84 44
92
24 332 629 225 27
A1 21 105 31 207
A197 A196 52
120 26 205
29 52 22
Key Trip Purpose 80 297
1 54
Commute 219 109 28
Business 27 20
Other 78
HGV 18 A192
30
Client: Northumberland County CouncilAM 2015 Do Minimum Unconstrained Model Flows
A1
148 56
199 77 0 32 N
97 1
137
0
379 58 A197
187 2 59 0 31
56 A192
135 10135 10
0 5 145
Mitford Rd A192 150 35 11 12 21 30 N
45 11 0 181
164 9 6 0
Coopies Lane 209 0 0 A192 241 19
43 27 A196 45 A197 383
209 11 309 56 22
0 160 0 190
135 28 29 0
49 85 244 14 350 227
106 0 62 263 60 0 20
0 10 116 96
0 106 231 174
13 0 70 0
349 6 16
73 239
194 46 497
3 0 169 270 15 100 116 538 18
24 5 65 0 424 112
225 136 17 0 327
0 0 A192 0
4 227 A192 294
36 23 52
226 272
0 0 401 314 25
330 84 0
66
24 309 488 226 27
A1 0 101 0 209A1
A197 A196 43
130 26 209
29 57 0
Key TripPurpose 81 135
0 49
Commute 233 106 28
Business 34 0
Other 79
HGV 0 A192
30
Client: Northumberland County CouncilAM 2015 Do Something Unconstrained Model Flows
A1
335 N
127 1
193
27
A197
509 2
59 A192
150 14150 14
20 4 269
Mitford Rd A192 149 22 12 12 21 64 N
54 10 0 212
161 9 57 22
Coopies Lane 205 7 1 A192 239 19
52 27 A196 42 A197 537
202 11 307 83 22
34 334 14 215
310 28 41 47
54 88 418 14 323 229
111 25 68 319 84 34 20
25 10 184 92
36 119 278 170
13 22 69 16
367 6 16367 6 16
80 394
234 57 511
3 41 213 284 15 103 137 693 18
53 5 72 45 411 123
248 137 17 54 369
22 41 A192 58
4 257 A192 313
41 23 59
219 314
17 41 379 286 25
368 82 44
90
24 319 627 222 27
A1 30 106 37 205
A197 A196 52
120 26 202
29 53 34
Key Trip Purpose 82 310
2 54
Commute 207 111 28
Business 34 25
Other 88
HGV 22 A192
30
Client: Northumberland County CouncilAM 2030 Do Minimum Unconstrained Model Flows
A1
200 92
202 79 0 32 N
93 1
142
0
396 76 A197
196 2 63 0 31
56 A192
162 10162 10
0 5 157
Mitford Rd A192 143 33 12 12 21 24 N
51 11 0 185
165 9 6 0
Coopies Lane 198 0 0 A192 239 19
49 27 A196 39 A197 382
207 11 323 56 22
0 176 0 194
137 28 33 0
49 89 244 14 330 227
111 0 62 264 59 0 20
0 10 123 93
0 107 236 175
13 0 68 0
343 6 16
72 238
192 46 480
3 0 170 267 15 99 113 533 18
24 5 66 0 419 106
227 137 17 0 332
0 0 A192 0
4 237 A192 293
38 23 52
229 274
0 0 387 311 25
330 82 0
65
24 309 486 231 27
A1 0 96 0 198A1
A197 A196 49
146 26 207
29 58 0
Key TripPurpose 83 137
0 49
Commute 215 111 28
Business 38 0
Other 82
HGV 0 A192
30
Client: Northumberland County CouncilAM 2030 Do Something Unconstrained Model Flows
A1
39 N
147 1
209
14
A197
60 2
155 A192
336 13336 13
11 13 107
Mitford Rd A192 42 5 21 12 21 125 N
64 6 0 354
157 9 11 23
Coopies Lane 42 19 0 A192 89 19
84 27 A196 96 A197 107
152 11 426 112 22
16 42 19 332
41 28 63 20
124 140 58 14 89 341
130 16 116 70 88 15 20
12 10 195 123
10 210 98 319
13 17 182 22
56 6 1656 6 16
80 78
206 157 164
3 12 69 65 15 252 243 136 18
94 5 98 13 631 219
261 269 17 40 550
15 22 A192 35
4 60 A192 83
83 23 121
217 299
15 21 115 408 25
98 187 37
144
24 387 99 404 27
A1 24 181 35 42
A197 A196 84
17 26 152
29 47 16
Key Trip Purpose 55 41
8 124
Commute 14 130 28
Business 39 12
Other 52
HGV 1 A192
30
Client: Northumberland County CouncilIP 2015 Do Minimum Unconstrained Model Flows
A1
27 58
30 74 0 32 N
105 1
191
0
25 64 A197
33 2 59 0 31
152 A192
283 9283 9
0 13 93
Mitford Rd A192 41 5 18 12 21 85 N
59 7 0 327
159 9 9 0
Coopies Lane 43 0 0 A192 88 19
79 27 A196 89 A197 96
153 11 404 92 22
0 34 0 302
33 28 54 0
108 128 29 14 89 345
117 0 96 51 88 0 20
0 10 150 84
0 166 95 318
13 0 153 0
44 6 16
70 65
174 149 146
3 0 50 57 15 252 203 107 18
76 5 93 0 597 193
227 262 17 0 492
0 0 A192 0
4 60 A192 71
72 23 110
217 264
0 0 115 409 25
81 167 0
125
24 354 86 383 27
A1 0 167 0 43A1
A197 A196 79
16 26 153
29 60 0
Key TripPurpose 59 33
0 108
Commute 20 117 28
Business 43 0
Other 60
HGV 0 A192
30
Client: Northumberland County CouncilIP 2015 Do Something Unconstrained Model Flows
A1
43 N
139 1
243
16
A197
61 2
155 A192
386 14386 14
14 14 120
Mitford Rd A192 37 5 23 12 21 128 N
66 6 0 377
161 9 12 27
Coopies Lane 34 22 0 A192 92 19
87 27 A196 96 A197 109
153 11 432 119 22
19 46 22 353
42 28 66 23
126 148 60 14 83 348
136 19 119 74 98 17 20
14 10 233 108
13 229 101 312
13 20 172 26
58 6 1658 6 16
84 80
205 166 161
3 14 72 68 15 260 238 141 18
96 5 103 16 635 225
263 277 17 48 562
18 27 A192 43
4 64 A192 86
78 23 125
222 302
18 26 110 413 25
101 182 45
148
24 392 103 418 27
A1 28 186 41 34
A197 A196 87
19 26 153
29 57 19
Key Trip Purpose 59 42
9 126
Commute 15 136 28
Business 41 14
Other 59
HGV 1 A192
30
Client: Northumberland County CouncilIP 2030 Do Minimum Unconstrained Model Flows
A1
31 70
32 77 0 32 N
104 1
218
0
29 87 A197
35 2 66 0 31
152 A192
347 10347 10
0 14 96
Mitford Rd A192 43 5 19 12 21 88 N
61 7 0 346
161 9 9 0
Coopies Lane 45 0 0 A192 91 19
81 27 A196 92 A197 99
153 11 417 96 22
0 34 0 317
34 28 58 0
116 131 30 14 98 348
119 0 96 47 91 0 20
0 10 174 82
0 164 99 305
13 0 153 0
44 6 16
73 74
172 153 151
3 0 51 60 15 258 205 111 18
78 5 98 0 577 198
211 267 17 0 495
0 0 A192 0
4 64 A192 72
74 23 113
219 268
0 0 120 409 25
83 168 0
129
24 341 88 388 27
A1 0 172 0 45A1
A197 A196 81
17 26 153
29 64 0
Key TripPurpose 66 34
0 116
Commute 21 119 28
Business 46 0
Other 69
HGV 0 A192
30
Client: Northumberland County CouncilIP 2030 Do Something Unconstrained Model Flows
A1
472 N
34 1
213
7
A197
329 2
132 A192
195 16195 16
7 8 466
Mitford Rd A192 291 21 13 12 21 67 N
19 6 0 254
71 9 16 12
Coopies Lane 231 8 2 A192 327 19
35 27 A196 69 A197 215
83 11 280 58 22
9 132 9 270
249 28 70 10
62 217 410 14 290 377
215 7 119 433 56 11 20
10 10 248 36
13 119 450 79
13 3 29 3
209 6 16209 6 16
53 243
273 86 727
3 3 277 225 15 228 91 553 18
57 5 66 9 356 161
205 261 17 15 585
9 10 A192 20
4 277 A192 484
69 23 108
130 293
7 10 637 242 25
372 77 17
50
24 223 405 429 27
A1 9 94 16 231
A197 A196 35
165 26 83
29 44 9
Key Trip Purpose 142 249
16 62
Commute 89 215 28
Business 29 10
Other 49
HGV 0 A192
30
Client: Northumberland County CouncilPM 2015 Do Minimum Unconstrained Model Flows
A1
267 72
240 41 0 32 N
31 1
212
0
84 58 A197
225 2 54 0 31
122 A192
177 15177 15
0 9 386
Mitford Rd A192 162 22 6 12 21 45 N
23 6 0 209
76 9 16 0
Coopies Lane 100 0 0 A192 328 19
40 27 A196 55 A197 170
89 11 278 37 22
0 122 0 242
216 28 55 0
50 201 314 14 275 341
197 0 103 258 55 0 20
0 10 186 36
0 104 343 111
13 0 46 0
172 6 16
52 208
270 72 640
3 0 265 196 15 208 108 496 18
45 5 48 0 358 132
156 229 17 0 547
0 0 A192 0
4 286 A192 458
70 23 108
141 296
0 0 540 275 25
392 99 0
60
24 193 377 386 27
A1 0 79 0 100A1
A197 A196 40
178 26 89
29 35 0
Key TripPurpose 132 216
0 50
Commute 89 197 28
Business 34 0
Other 53
HGV 0 A192
30
Client: Northumberland County CouncilPM 2015 Do Something Unconstrained Model Flows
A1
457 N
34 1
264
8
A197
420 2
129 A192
200 16200 16
8 8 491
Mitford Rd A192 295 22 15 12 21 66 N
19 7 0 263
73 9 16 14
Coopies Lane 228 10 2 A192 323 19
36 27 A196 69 A197 271
84 11 269 58 22
11 138 11 272
250 28 72 12
65 228 454 14 283 391
222 9 116 415 54 13 20
12 10 255 38
15 130 426 87
13 4 32 3
187 6 16187 6 16
53 282
253 83 710
3 3 257 281 15 237 94 582 18
55 5 67 10 380 157
217 273 17 19 566
11 11 A192 23
4 274 A192 458
71 23 103
137 263
8 12 609 244 25
358 77 20
53
24 240 434 438 27
A1 10 95 20 228
A197 A196 36
216 26 84
29 46 11
Key Trip Purpose 153 250
19 65
Commute 91 222 28
Business 30 12
Other 52
HGV 4 A192
30
Client: Northumberland County CouncilPM 2030 Do Minimum Unconstrained Model Flows
A1
281 93
238 42 0 32 N
32 1
251
0
148 66 A197
256 2 55 0 31
122 A192
185 16185 16
0 10 399
Mitford Rd A192 169 21 7 12 21 45 N
23 6 0 210
79 9 16 0
Coopies Lane 102 0 0 A192 318 19
41 27 A196 55 A197 168
90 11 268 38 22
0 129 0 240
236 28 59 0
51 213 340 14 257 350
206 0 101 257 51 0 20
0 10 183 38
0 100 351 120
13 0 50 0
179 6 16
53 231
262 73 625
3 0 247 209 15 217 107 515 18
40 5 49 0 363 134
163 232 17 0 537
0 0 A192 0
4 290 A192 470
74 23 109
148 287
0 0 542 278 25
380 100 0
55
24 199 389 391 27
A1 0 77 0 102A1
A197 A196 41
186 26 90
29 36 0
Key TripPurpose 136 236
0 51
Commute 99 206 28
Business 38 0
Other 55
HGV 0 A192
30
Client: Northumberland County CouncilPM 2030 Do Something Unconstrained Model Flows
Appendix C – Location Plan
A19
A1A9
A1068
A1
A197A192
A196
A196
A1068
A1147
A1
ASHINGTON
BEDLINGTON
BLYTH
NEWBIGGIN-BY-THE-SEA
MORPETH
A4
cm
Client:
Project:
Location Plan
A1-SENSLR-MNB
Title:
No. FIGURE 1
Design:
Chk'd:
Date:
Rev:
CAD:
App'd:
Scale:
LS
GP
July ’11
LS
SM
NTS
www.aecom.comFax: +44 (0) 191 224 6599Tel: +44 (0) 191 224 6500First Floor,
One Trinity Gardens, Quayside,NEWCASTLE UPON TYNE, NE1 2HF
Newcastle7 miles
Key:Morpeth NorthernBypass
Pegswood Bypass
Appendix D – Area Network Plan
A4
cm
Client:
Project:
Area Network Plan
A1-SENSLR-MNB
Title:
No. FIGURE 2
Design:
Chk'd:
Date:
Rev:
CAD:
App'd:
Scale:
LS
GP
July ’11
LS
SM
NTS
www.aecom.comFax: +44 (0) 191 224 6599Tel: +44 (0) 191 224 6500First Floor,
One Trinity Gardens, Quayside,NEWCASTLE UPON TYNE, NE1 2HF
Appendix E – Morpeth Network Plan
A4
cm
Client: Project: Title:
No.Design:
Chk'd:
Date:
Rev:
CAD:
App'd:
Scale:
LS LS
SCALEJuly ’11 REVGP SM
A1-SENSLR-MNB
FIGURE 3
Morpeth Network Plan
www.aecom.comFax: +44 (0) 191 224 6599Tel: +44 (0) 191 224 6500First Floor,
One Trinity Gardens, Quayside,NEWCASTLE UPON TYNE, NE1 2HF