A New Policy Sensitive Travel Demand Model

for Tel Aviv

Yoram Shiftan

Transportation Research Institute

Faculty of Civil and Environmental Engineering

The Technion

The Israel Regional Science AssociationJune 21, Haifa University

2

Introduction and Motivation

Need for a policy-sensitive model

Range of transportation policies under study:• Congestion pricing

• Parking policies

• Land use and growth management

• Highway and transit improvements

Need for an integrated appraisal for air quality, environmental impact assessment, and induced demand

Tour models can capture complex travel behavior patterns better than traditional models

3

Home

Work

Dinner

Tour-based Approach:Two Inter-related Tours

ShoppingTravel is a derived demand from the demand for activities

4

Space

At home

At work

At store

At home

At home

At dinner

Travel to work

Travel to store

Travel to home

Travel to dinner

Travel to home

Tim

e

H

W

S

D

H

H

Example of a Daily Travel Pattern

5

Trip-based Approach:Five Independent Trips

Home-based Work

Non-home Based

Home-based Shop

Home-based Other

Home-based Other

H

W

S

DH

H

WS

H

D

9

Review of the Current Tel Aviv Model System

A trip-based model

Traditional model components

• Four-step model – trip generation, trip distribution, mode choice and network assignment

Designed for evaluating mass transit alternatives

• Sophisticated mode choice model development

• Lack of level of service variables in trip generation

• Reliance on a gravity model for trip distribution

10

Review of the Tel-Aviv Model System

“Best practice” tour-based model system

Builds on existing data sources• National travel diary survey (NTHS)• Mass transit stated preference survey (NTA)

Reliance on new surveys• Parking supply survey• Rail corridor random survey• Tour-based stated-preference survey

Other enhancements• Revised transit and highway networks• Refined level of service estimates• Zone attributes based on NTA’s approach

Policy Sensitive

Can account for induced demand

11

The Data

A three-day trip diary (NTHS)

An extension of the NTHS in communities adjacent torail corridors

A stated-preference survey conducted for a previous study to analyze the potential for a new rapid transit system

A tour-based stated-preference survey designed and conducted for this study

A detailed parking survey that includes information on demand and supply

12

The Stated-Preference Survey

Details about one’s actual tour

Various auto restraint policies

• Congestion pricing

• Parking pricing

Various alternative responses

• Change mode/access mode

• Change number of stops

• Change time of travel

6 choice experiments per respondent

16

Main Activity

Main Destination

Work Education Shopping Other No tour

Dest 1 Dest 2 Dest 3 Dest 100 Dest 1219

Automobile Ownership

Zero One Two +

Time of Day

cCombination of arriving to and departure from main acitivity

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Tour Main Mode

Revealed-preference: NTHS & Rail Corridor surveyStated-preference: New SP survey & NTA survey

Taxi Driver Pass. Bus Rail Employer Transport

P&R, K&R,Walk, Bus

P&R, K&R,Walk

“Before Stop” Type / “After Stop” Type

Work Education Shopping Other No stop

No stops Before After Before and After

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“Before Stop” Mode / “After Stop” Mode

Taxi Driver Pass. Bus Rail

“Before Stop” Destination / “After” Stop” Destination

Same mode Otheras in the Tour

Dest 1 Dest 2 Dest 3 Dest 100 Dest 1219

“Before Stop” Arrival time / “After” Stop” Departure time

19

Model Application Program

Proposed approach• Sample enumeration• Monte Carlo simulation• Incremental approach

Practical considerations• Validation standards and targets• Simplifications in the model structure• Tradeoffs between model sensitivity and model run times

Flexible and modular architecture

Ability to run individual model components

Ability to apply with different sample sizes

20

Model Application Program

Representative Population

Activity-basedModels:

Tours / Destinations / Stops / Modes

NetworkAssignment

Zonal dataNTHS

Census

LOS Data

De-compose Tours

Segment time of Day and mode

External tripsTruck tripsBus trips

O-D Trip Tablesby Mode and by

Time of Day

Auto Ownershipmodel

21

Policy Evaluation: Congestion Pricing

Policy: Introduce congestion pricing in an area, a

corridor, or a facility during different times of day

Potential impacts on:

• Tour generation

• Share of different modes

• Traffic levels on alternate route(s)

• Distribution of travel by time of day

23

Potential Response to Congestion Pricing

24

What reactions to Congestion Pricingcan different models capture?

New Model Trip Model

Cancel a trip or reduce total number of trips Yes

Delay departure time for work-related travel Yes

Change mode for one or more trips/tours Yes Yes

Combine trips by increasing number of stops Yes

Change mode and departure time Yes

Shift most non-work trips to of-peak time periods

Yes

Change route choices in response to pricing Yes Yes

Change destination Yes

25

Parking Policies

Parking cost increase by region or time of day

Reduced parking supply

Prohibited parking zones

Park and Ride/Kiss and Ride

Time limits

Parking location (walk time)

27

What reactions to Parking Policiescan different models capture?

New Model Trip Model

Cancel a trip or reduce total number of trips

Yes

Delay departure time for work-related travel

Yes

Change mode for one or more trips/tours

Yes Yes

Combine trips by increasing number of stops

Yes

Change mode and departure time Yes

Shift most non-work trips to off-peak time periods

Yes

Change destination Yes

28

Land Use and Growth Management Policies

Land development incentives around fixed

transportation infrastructure

Concentrated vs. dispersed development

Transit Oriented Development

29

What reactions to Land Use and Growth Management can different models capture?

New Model Trip Model

Increase stops / combine trips with dense mixed development

Yes

Concentrate trips with transit-oriented development

Yes

Increase transit market share with service improvements

Yes Yes

Reduce length of travel due to mixed development patterns

Yes Yes

Account for attractiveness of different zones in study area

Yes

30

Highway and Transit Improvements

Increase transit investment in different corridors

Traffic management

HOV lanes/Busways

Road development

31

What reactions to Highway and Transit Improvements can different models capture?

New Model Trip Model

Increase trip making (induced demand) to better served areas

Yes

Shift travel to areas with improved accessibility

Yes

Increase transit market share with service improvements

Yes Yes

Reduce highway travel times and increase auto share

Yes Yes

32

Model Capability Summary

More policies can be analyzed

• Parking supply and congestion pricing

More impacts can be analyzed

• Trip chainning, change destination, cancel trip.

Account for induced demand

Provide more realistic response to policies

Provide better input for air quality analysis

• Enable estimation of cold and hot starts