Transportation leadership you can trust.

presented to

12th TRB National Transportation Planning Applications Conference

presented by

Arun Kuppam, Cambridge Systematics, Inc.

co-authored by

Philip Johnson, Dallas Area Rapid Transit

Thomas Rossi, Amlan Banerjee, Saurabh Kumar, Cambridge Systematics

May 19, 2009

Visitor Travel Model, Special Events Model and Parking Location Choice Model for Studying Transit ImprovementsDowntown Dallas Transit Study

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Objectives

To better understand travel behavior of various travel markets to enable examination of a range of transit improvements in Downtown Dallas

Hotel visitor travel

• Survey – Downtown Dallas hotel survey

• Models – Trip generation, destination choice, mode choice

Special events travel

• Survey – Special events survey at AA and Meyerson Centers

• Models – Destination choice and mode choice

Parking location choice

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Project Status

Visitor models - Complete

Special event models - Under development

Parking location choice model – To be developed in June

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Visitor Travel ModelSurvey Data

Total interviews – 910; Useable records – 896

Large hotel ( 600+ rooms ) : 296

Medium hotel ( 200 – 599 rooms ) : 336

Small hotel ( < 200 rooms ) : 264

Male – 53%; Female – 47%

Business visitors – 83%; Leisure visitors – 17%

Arrival to Dallas – Airplane: 79% Private vehicle: 17%

Arrival to hotel from airport – Shuttle: 38% Taxi: 29% Rental car: 21%

Transit < 1%

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Visitor Travel ModelOverview

General structure

Trip production model – trip rate per hotel room for business and leisure travelers

Trip attraction model – separate regression models for business and leisure travelers Trip attractions = B1 * zonal employment + B2 * zonal pop + ….

Destination choice – four multinomial logit models CBD (business, leisure); Non-CBD (business, leisure)

Mode choice – nested logit models Business visitor and leisure visitor models

Relationship to NCTCOG model Source of hwy and transit LOS skims – IVT, OVT, Dist, Cost

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Visitor Travel ModelTrip Production

Trip rates per hotel room

Eat Meal Other Business NHB ALL

Business 0.83 0.36 0.91 0.10 2.20

Leisure 0.57 1.51 0.06 0.40 2.53

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Visitor Travel ModelTrip Attraction

CBD Model

• Business Visitors Trip attractions = 0.157 * Service Employment

• Leisure Visitors Trip attractions = 0.101 * Service Employment

Non-CBD ModelTrip Purpose Percent Trips

Attracted to CBDPercent Trips

Attracted to Non-CBD

Hotel based meal 64% 36%

Hotel based business 79% 21%

Hotel based other 40% 60%

Non-hotel based 49% 51%

TOTAL 62% 38%

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Visitor Travel ModelDestination Choice: Specification

Estimated models

CBD model (Business, Leisure)

Non-CBD (Business, Leisure)

Multinomial Logit Specification

Utility of zone ‘i’:

Xki= zonal attributes, LOGSUM computed from MC model

= utility of modal alternative k from zone i to zone j computed from the mode choice model

nini2i2i1i1ii XB....XBXBU

k

ijkij )exp(UlnLOGSUM

ijkU

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Visitor Travel ModelDestination Choice: Estimation Results

CBD Model Business Leisure

Variable Coeff t-stat Coeff t-stat

Logsum 0.998 5.54 0.475 4.58

Distance -0.374 -2.67

log of trip attraction (size variable) 1.00 Fixed 1.00 fixed

rho2 w.r.t. zero 0.174 0.132

Non-CBD Model Business Leisure

Variable Coeff t-stat Coeff t-stat

Logsum 0.309 2.19 1.350 3.57

Square of logsum 0.204 1.47 0.630 3.10

Cube of logsum 0.106 2.24 0.096 2.99

log of trip attraction (size variable) 1.00 fixed 1.00 fixed

rho2 w.r.t. zero 0.101 0.103

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Visitor Travel ModelMode Choice: Specification

Two estimated models

Business visitor model and Leisure visitor model

Nest Structure

Model Variables

LOS = IVT + K1 * OVT+ K2* COST

Inter-zonal Distance (miles)

Auto availability

CBD

Auto Walk Shuttle Taxi Transit

Bus Light Rail

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Visitor Travel Model Mode Choice: Estimation Results

Business Visitors Model

Transit nest coefficient = 0.33 (4.4)

VOT = $4.62/hr

Variable Auto Shuttle Rail Bus Taxi Walk

Constant -2.73 (-9.1) 0.353 (4.7) -0.235 (-3.2) -0.731 (-3.2) 0.777 (4.0)

LOS (min) -0.020 -0.020 -0.020 -0.020 -0.020

Distance (miles) -3.15 (-9.3)

Auto availability -1.45 (-6.3) -0.286 (-3.6) -0.286 (-3.6) -1.45 (-6.3) -1.45 (-6.3)

CBD 3.17 (12.0) 1.09 (3.9)

rho2 (0) = 0.298

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Visitor Travel Model Mode Choice: Estimation Results

Leisure Visitors Model

Transit nest coefficient = 0.67 (2.0)

VOT = $2.45/hr

Variable Auto Shuttle Rail Bus Taxi Walk

Constant -3.89 (-9.0) -0.361 (-1.7) -1.09 (-5.1) 0.708 (2.8) 1.03 (1.1)

LOS (min) -0.020 -0.020 -0.020 -0.020 -0.020

Distance (miles) -4.12 (-7.0)

Auto availability -1.79 (-6.4) -1.68 (-5.8) -1.68 (-5.8) -1.79 (-6.4) -1.79 (-6.4)

CBD 2.54 (4.0) 1.76 (2.6)

rho2 (0) = 0.319

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Special Events ModelSurvey Data

Completed Interviews

American Airlines Center – 548

Meyerson Center – 411

88% came downtown only for the event

Trip origin

In the City of Dallas – 27%

Outside Dallas – 73%

Mode Choice

Auto – 89% Transit – 7%

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Special Event ModelOverview

Origin/Destination choice model

Multinomial logit model

Given small sample size, market segmentation may not be plausible

Mode choice model

Auto dominant mode of arrival; estimation of mode choice model possible without market segmentation

Binary logit model (auto vs. transit)

Relationship to NCTCOG model

Source of highway and transit LOS skims – IVT, OVT, distance, cost

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Parking Location ModelOverview

Model will be developed using logit formulation for auto trips to Dallas Downtown

To be integrated with NCTCOG mode choice model

Model will also include trips intercepted outside downtown and continue to the destination using transit

Variables to be considered (NCTCOG model):

Total travel time

Walk time to destination

Number of transfers

Transit wait time

Parking cost and transit fare

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Next Steps

Models will be validated using weighted survey data and other sources of travel data

All the demonstrated model components being implemented using TransCAD GISDK script

TransCAD programming will be consistent with and use the NCTCOG zonal and network database