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First published online January 1, 2012

Behavioral Analysis of Decisions in Choice of Commercial Vehicular Mode in Urban Areas

Abstract

The decisions of vehicular mode choice by businesses and commercial sectors in urban areas are addressed with attention to the unique trip-chaining behavior of commercial vehicles. Travel diary data from a collection of large-scale commercial vehicles in the Denver, Colorado, metropolitan area were used for analysis. Four types of travel activities were surveyed: business meetings, pickup and drop-off of people, pickup and delivery of cargo, and service calls. The survey results indicated that automobiles, pickup trucks, sport utility vehicles, single-unit trucks, and combination trucks were the main vehicular modes for travel with commercial purposes. The original survey data were sorted into trip-based and tour-based data sets for measuring commercial vehicle travel activities. A “trip” is defined as travel from one stop to another, and a “tour” is an entire travel journey starting from and ending at the home base of a vehicle with visits to various locations of interest. Discrete choice modeling techniques, particularly multinomial logit and nested logit models, were used to quantify the relationship between decisions on the choice of commercial vehicular mode and their affecting factors, and the two data sets were used separately. The modeling results indicate that mode choice by the commercial sector is travel specific, territory dependent, and cargo sensitive and varies by company. As proved by the comparison of trip-based and tour-based models, the tour is an intuitively and quantitatively better unit for measuring the travel activities of commercial vehicles and for modeling behavior of mode choice of the commercial sectors.

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Article first published online: January 1, 2012
Issue published: January 2012

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© 2012 National Academy of Sciences.
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Qian Wang
231 Ketter Hall, Department of Civil, Structural, and Environmental Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260-4300.
Jinge Hu
204 Ketter Hall, Department of Civil, Structural, and Environmental Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260-4300.

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