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T Copula VMT 6March09





A COPULA-BASED JOINT MULTINOMIAL DISCRETE-CONTINUOUS MODEL OF
VEHICLE TYPE CHOICE AND MILES OF TRAVEL
Erika Spissu University of Cagliari - Italy
CRiMM - Dipartimento di Ingegneria del Territorio Via San Giorgio 12, 09124 Cagliari Tel + 39 070 675 6403; Fax + 39 070 675 6402 Email espissu@unica.it
Abdul Rawoof Pinjari University of South Florida Department of Civil & Environmental Engineering
4202 E. Fowler Avene, ENC 2503, Tampa, FL 33620 Tel (813) 974-9671; Fax (813) 974-2957 Email apinjari@eng.usf.edu
Ram M. Pendyala Arizona State University Department of Civil and Environmental Engineering Room ECG, Tempe, AZ 85287-5306 Tel (480) 727-9164; Fax (480) 965-0557 Email ram.pendyala@asu.edu
Chandra R. Bhat (corresponding author)
The University of Texas at Austin Department of Civil, Architectural & Environmental Engineering
1 University Station, C, Austin, TX 78712 Tel (512) 471-4535; Fax (512) 475-8744 Email bhat@mail.utexas.edu


ABSTRACT
In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete-continuous model system formulated in this study explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e., self-selection effects. Anew copula-based methodology is adopted to facilitate model estimation without imposing restrictive distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components. The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation approaches for joint discrete-continuous model systems. The model system, when applied to simulate the impacts of a doubling in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.
Keywords: vehicle type choice, vehicle usage, vehicle miles of travel, copula-based approach, discrete- continuous choice modeling, travel behavior, greenhouse gas emissions, transportation energy consumption


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