understanding service changes of transit agencies for modelling the bus transit network evolution

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Understanding Service Changes of Transit Agencies for Modelling the Bus Transit Network Evolution. Amr M. Mohammed 1 Amer Shalaby 2 Eric J Miller 3 1: Morrison Hershfield Ltd. 2,3: Dept . of Civil Engineering , University of Toronto - PowerPoint PPT Presentation

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P-TRANE

Understanding Service Changes of Transit

Agencies for Modelling the Bus Transit Network

EvolutionAmr M. Mohammed1

Amer Shalaby2

Eric J Miller 3

1: Morrison Hershfield Ltd.2,3: Dept. of Civil Engineering, University of

Toronto

Paper presented at the 2011 GIS in Public Transportation Conference

URISA – The Association of GIS Professionals

September 15th 2011

Mohammed, Shalaby and Miller

P-TRANE

Overview Introduction Bus Network Evolution Model Phase I: Mississauga Transit Types of Changes Phase II: P-TRANE Results Conclusions and Recommendations Current Developments(City of Ottawa: Hospital Link, LRT)

Mohammed, Shalaby and Miller

P-TRANE

Introduction Bus operators/agencies Constantly

Adjust networks (changes)

Behaviour

Response to: Dynamic of Ridership Changes & Budget

Mohammed, Shalaby and Miller

P-TRANE

Introduction Model captures changes over time:

Predict network shape & functionality Future Time steps Aid for developers, Transit & urban planners Component in urban-transportation

demand simulation frameworks (e.g. ILUTE)

Mohammed, Shalaby and Miller

P-TRANE

IntroductionP-TRANE

“Changes triggered by socioeconomic & Urban factors (Land-Use) & dictated/Guided by service standards practices”Two-phase

Empirical Study (Multiple regression & simultaneous equations) – USING ArcGISService Standards (P-TRANE) - USING ArcGIS

Mohammed, Shalaby and Miller

P-TRANE

IntroductionFits into ILUTE? Transportation Planning Models Bring transportation-related components of

urban systems into integrated modelling framework

Urban Form Transportation

Model 2-way interactions

Integration

Mohammed, Shalaby and Miller

P-TRANE

Introduction: ILUTEIntegrated Land-Use, Transportation, Environment

(Salvini and Miller, 2005)

Travel Demand

Household/Person decisionsActivity of Objects (Persons/hh/firms/job market)

Travel Times Energy UseEmissions

Exogenous

Mohammed, Shalaby and Miller

P-TRANE

Bus Evolution ModelPhase I: Empirical analysis

Supply historical trends Macroscopic Mutual effect between Demand & Supply ‘Demand and supply are recursive & simultaneous’ (e.g.

Taylor & Miller 2003, Peng 1997)

Phase II: P-TRANE GIS of bus network growth Microscopic (bus line /period/branch detail) Service Standards

Mohammed, Shalaby and Miller

P-TRANE

PHASE I Analysing historical trends of transit supply

Purpose: Understand causes and triggers of growth

Statistical and econometric models

Phase I: Mississauga Transit

Demand?Population?

Income?

Demographics?

Mohammed, Shalaby and Miller

P-TRANE

Phase I: Mississauga Transit

Mississauga

Downtown Toronto – Business Centre

City of Mississauga

Subway Stations (Western Terminus)Kipling/Islington

Busy

Explosive Growth

Employment Centre

Connectivity

Mohammed, Shalaby and Miller

PREMOTRANE

Phase I: Mississauga Transit• Demographic

and socioeconomic variables• ArcGIS (1/4 mile buffer zone) (Local & City wide)

• Multiple time steps (1986-2001) (Census Tract + TTS zones data)

• Multiple Regression & simultaneous equations

• Transit supply → bus frequencies (Dependant variable)

Phase I: Results

Bus Frequency = -2.623 + 0.00316 (Demand {ridership}) + 0.604 (Transfers) + 4.916 (Dummy variable representing the connection to TTC subway) + 0.001613 (Population Density) – 0.001 (No of Children) + 7.166 * 10-5 (City-wide No of Children)

Cross-sectional models using Multiple Regression

Phase I: ResultsSimultaneous Regression Equations

Bus Frequency = -12.854 + 0.01394 (Demand) + 0.1661 (Labour Force) + 0.3 (No of Transfers) + 2.093 (Dummy variable representing the connection to TTC subway) --------------------------------------------------------------------------Demand = -130.83 + 0.1003 (Density) + 0.0147 (Employment) + 0.127 (Change in City-wide Density) – 0.05635 (Number of Children) + 48.214 (Bus Frequency {last period})

Phase I: ResultsSimultaneous Regression Equations: Model Testing

• 2001 data(Observed vs. Estimated)

• 2-tailed matched pairs, difference not significantly different from zero

• Previous model show strong predictive power

0

2

4

6

8

10

12

14

16

Freq

. (bu

s/ho

ur)

Corridors

(6-a) Observed and Predicted Frequencies

0

100

200

300

400

500

600

700

Dem

and.

(Pas

s/ho

ur)

Corridors

(6-b) Observed and Predicted Demand

Mohammed, Shalaby and Miller

P-TRANE

Transit Evolution ModelPhase II

“Prediction Model of Transit Network Evolution”

Previously PREMOTRANE

P-TRANE

Mohammed, Shalaby and Miller

P-TRANE

P-TRANE

1- Capital-intensive changes Political – Large Scale (subway, LRT) –

Effects 2 Exogenous

Phase II: Types of Changes

Types of Bus Network Changes

2- Periodic Service changes Regular, (medium to small) Reaction to Changing demands Budget is exogenous

Extra subsidy? = No new buses into P-TRANE

Modeled in P-TRANE

New bus route

Route removal

Frequency change

Re-routing & Extending

Mohammed, Shalaby and Miller

PREMOTRANE

P-TRANE

2- Medium to Small Periodic Service changes

Phase II: Types of Changes

Mohammed, Shalaby and Miller

P-TRANE

Service Standards:

• Guidelines• Service quality & financial performance

• Proposals for new service

• Rules into P-TRANE

• Expert Systems (KB: Service Standards Rules + Priority Rules)

Frequency, Financial Performance

P-TRANE

Phase II: TTC Service Standards

Phase II: P-TRANE , Minor changes: Bus Crowding RuleP-TRANE

IF:

Ridership during the busiest hour period is greater than loading standard (peak or off peak)

THEN:

this route is flagged and will have service increase in the next time step

Financial Performance ruleFinancial Performance = Ridership / Operating cost

IF: Financial Performance < 0.23

THEN:

List route as financially poor, Order the list, Flag for reduction and use if needed for

other service improvements

This route is flagged and could be reduced (decrease frequency) or eliminated at the next time

step

PREMOTRANE

Implementation: Minor ChangesPhase II: PREMOTRANE

P-TRANE

Implementation: Minor ChangesPhase II: P-TRANE

Algorithm (1): Frequency increase and decrease in P-TRANE for minor changes.

Calculating frequencies from headways:F = 60 / H

1. Frequencies are increased or decreased by one bus/hour in each service iterationFN = F + 1 (Service increase: overcrowding)

FN = F – 1 (Service reduction: poor financial performance)2. Unit change in frequency is equivalent to an increase in number of buses by one (approximation).

NBN = NB + 1 (Service increase: overcrowding)NBN = NB – 1 (Service reduction: poor financial performance)

3. Run crowding check for lines that experienced frequency increase to check if demand was satisfied, if not, then go to step (2) (if more than one bus is required for any line at a time step). Iterate until demand is satisfied.

For each line requiring frequency reduction:IF NB = 1 (Only one bus operating, assumed service frequency).

Then Flag this line for removal for the next time period, if the area is only covered by this line, it is assumed to be re-built using Module 2 of P-TRANE.

For each line requiring frequency increase:NBN = NB + nHN = 60 / FN

IF HN < 1.5 minutes (Maximum frequency for buses).Then Do nothing and stop

(No service increase in this process, keep service frequency and do not update.)

Where:F : Bus frequency (bus/hour)H : Bus headway (in minutes)HN : New (updated) bus headway (in minutes)FN : New (updated) bus frequency (bus/hour)NB : Number of buses per line per time periodNBN : New (updated) number of buses per line per time periodn : Number of successful iterations (number of added buses)

Phase II: P-TRANE,GISMedium Changes

RulesP-TRANE

Serve people beyond 300 m of current service Maximise interconnection with rapid transit

stations Result an overall benefit for customers. Proposal presented by customers or

councillors in the area Service Gaps + Land-use (input) +

Developments (more likelihood)

P-TRANE,GIS : build new routes

PREMOTRANE

Phase II: P-TRANE,GISImplementation: Route Changes

P-TRANE

Phase II: P-TRANE,GISImplementation: Route Changes

Mohammed, Shalaby and Miller

PREMOTRANE

Modelling Procedure (Proposals)

PREMOTRANE

new line/extension/adjustment in routing

Modelling Procedure (Proposals)

P-TRANE

Line Builder in P-TRANEApply/add to updated network

Mohammed, Shalaby and Miller

P-TRANE

Transit Evolution ModelP-TRANE & ILUTE exchange demand, land-

use and supply data for future time steps and are simulated together.

P-TRANE

Demand (Ridership)

Land-use

P-TRANE

ILUTE

Socio-Economic Data

Transit Network (Supply)

P-TRANE

Phase II: P-TRANERelationship with ILUTE

Mohammed, Shalaby and Miller

PREMOTRANE

Results (Minor Changes)P-TRANE

Frequencies and Financial performance

Test 2005 network (TTC) Output: A number of lists of changes in

frequency & financially poor lines for 2006.

97% of actual # changes modelled by P-TRANE actually changed

ResultsP-TRANE

Route ChangesSheppard Subway stations - 2002 TTC made 11 changes - 3 new lines

Don Mills to Scarborough town Centre Finch East to Don Mills Victoria Park via consumers road (To Don Mills station)

P-TRANE output: Don Mills to Ellsemere station (one station south of

actual) Bayview to Finch (but through local streets) Bessarion to Finch (through local streets)

Spatial comparison Functionality / Spatially equivalent

Actual →

← P-TRANE

ResultsP-TRANE

Route ChangesSheppard Subway stations – 2002

ConclusionsP-TRANE

P-TRANE For the first time, Transit network

evolution Two phase project (empirical & DSS) P-TRANE – a (GIS) framework Simulates changes spatially and

temporally Predictive model, describes service

standards Component in ILUTE, GIS, User-friendly, Promising Results

Mohammed, Shalaby and Miller

P-TRANE

ConclusionsP-TRANE

P-TRANE DSS For Transit Agencies (e.g. TTC,

OCTranspo) Test future policies, alternatives,

standards Simulates Periodic Changes of

Service/Feeder Bus Routes Prior to (Capital Intensive) Projects

E.g., New LRT BRT, Subway Stations,

Mohammed, Shalaby and Miller

P-TRANE

Current DevelopmentsP-TRANE

Ottawa Transit: (LRT & Hospital Link BRT) Effects on feeder bus network;

Testing, validating and updating;

Next Steps Effects of Labour Unions Budget Model

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