Investigation on Latent Factors Affecting Route Diversion Intentions

Abstract

Advanced Traveler Information Systems (ATIS) have the potential to mitigate freeway congestion. The success of ATIS depends to a great extent on understanding drivers' route switching behavior. This route diversion behavior is a complex process that depends on situational constraints, socioeconomic characteristics of motorists, and latent individual characteristics. Three latent factors, namely risk acceptance, trust in traffic information provided, and expectation level of quality of information provided, were identified in this study. These latent factors, as well as socioeconomic characteristics and situational constraints, were incorporated in a binary logit model of stated route diversion intentions. It is observed that the latent factors were statistically significant explanatory variables of the drivers' stated route diversion intentions.