Development of a Mixed Multi-Nomial Logit Model to Capture the Impact of Information Systems on Travelers' Switching Behavior

Abstract

The continuous growth of road traffic increases the delays that road users face and negatively affects the overall transportation system performance. Advanced Traveler Information Systems (ATIS) may offer significant benefits in terms of improving the travel experience of individuals, but their impact on individuals' travel behavior and on the whole transportation system mainly depends on how travelers respond to the acquired traffic information. This article presents a case study on travelers' response to traffic information for the Puget Sound Region (PSRC). The data used come from travel diaries (collected in 2000), in which individuals were asked about the traveler information sources consulted on each trip and how the information was used. Traveler information sources, available in the region, encompass both conventional forms of information, such as radio traffic reports and advanced traveler information systems, for example, variable message signs (VMS) and websites. The objective of this study is to examine the impact of information acquisition on switching travel behavior. Two models have been estimated: a multinomial logit model (MNL) and a mixed multinomial logit model (MMNL) that accounts for correlation among observations from the same individuals in the data set. The estimated models show that travel pattern characteristics, the time of information acquisition (pretrip vs. en-route), the source, and the content of provided information significantly affect commuters' response to information.