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Transportation leadership you can trust.

Visitor Travel Model, Special Events Model and Parking Location Choice Model for Studying Transit Improvements Downtown Dallas Transit Study. Transportation leadership you can trust. presented to 12th TRB National Transportation Planning Applications Conference

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Transportation leadership you can trust.

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  1. Visitor Travel Model, Special Events Model and Parking Location Choice Model for Studying Transit ImprovementsDowntown Dallas Transit Study Transportation leadership you can trust. presented to12th TRB National Transportation Planning Applications Conference presented byArun Kuppam, Cambridge Systematics, Inc. co-authored byPhilip Johnson, Dallas Area Rapid Transit Thomas Rossi, Amlan Banerjee, Saurabh Kumar, Cambridge Systematics May 19, 2009

  2. 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

  3. Project Status • Visitor models - Complete • Special event models - Under development • Parking location choice model – To be developed in June

  4. 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%

  5. 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

  6. Visitor Travel ModelTrip Production Trip rates per hotel room

  7. Visitor Travel ModelTrip Attraction • CBD Model • Business Visitors • Trip attractions = 0.157 * Service Employment • Leisure Visitors • Trip attractions = 0.101 * Service Employment • Non-CBD Model

  8. 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

  9. Visitor Travel ModelDestination Choice: Estimation Results

  10. Visitor Travel ModelMode Choice: Specification Auto Taxi Transit Walk Shuttle Bus Light Rail • 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

  11. Visitor Travel ModelMode Choice: Estimation Results • Business Visitors Model • Transit nest coefficient = 0.33 (4.4) • VOT = $4.62/hr

  12. Visitor Travel ModelMode Choice: Estimation Results • Leisure Visitors Model • Transit nest coefficient = 0.67 (2.0) • VOT = $2.45/hr

  13. 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%

  14. 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

  15. 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

  16. 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

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