University of California Transportation Center

Increasing efforts in Advanced Traveler Information Systems has emphasized the need to develop more robust models of enroute driver behavior. The complexity in modeling driver behavior stems from the need to capture the day-to-day dynamics of choice, model diversion and active information acquisition, and account for individual preferences and needs. Previous papers by the authors discussed a conflict arousal methodology for modeling driver behavior in the presence of real-time information. It was posed that observed changes in enroute driver behavior, characterized by diversion or active information acquisition, are evoked through latent factors of conflict arousal and motivation. In-laboratory interactive simulation was used to collect enroute behavior data. This paper presents a structural equation approach for modeling enroute driver behavior and explaining causal factors of diversion and information acquisition as well as the interrelationship between these observed behaviors.