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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
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
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
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 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%
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
nini2i2i1i1ii XB....XBXBU
k
ijkij )exp(UlnLOGSUM
ijkU
9
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
10
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
11
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
12
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
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