Cross-Nested Joint Model of Travel Mode and Departure Time Choice for Urban Commuting Trips: Case Study in Maryland–Washington, DC Region

Abstract

The aim of this paper is to contribute to describe the simultaneous choice of travel mode and departure time by making use of a cross-nested logit structure that allows for the joint representation of interalternative correlation along the both choice dimensions. Traditional multinomial logit model and nested logit model are formulated respectively. The analysis uses the revealed preference data collected from Maryland-Washington, DC, regional household travel survey during 2007–2008 for commuting trips, considering more work-related characteristics than previous studies. A comparison of the different model results shows that the presented cross-nested logit structure offers significant improvements over multinomial logit and nested logit models. The empirical results of the analysis reveal significant influences on commuter joint choice behavior of travel mode and departure time. Moreover, a Monte Carlo simulation for two groups of scenarios arising from transportation policies, congestion pricing, and improvements to transit service during peak period is undertaken respectively to examine the impact of a change in car travel cost and transit travel time on the travel mode and departure time switching. The simulation results show that US$5 increase in car travel cost during peak period has a similar effect on reducing drive alone in peak hours as 30% saving in transit travel time but only half of the latter policy in the transit ridership increase.