MODELING DRIVERS’ STATED ENROUTE SWITCHING BEHAVIOR UNDER VARIOUS INFORMATION SCENARIOS

Abstract

Advanced Driver Information Systems can benefit drivers by switching routes while encountering traffic congestion to alleviate congestion. Therefore, it is important to realize the latent variables of real-time traffic information that affect drivers’ enroute switching behavior. This paper identified the latent variables that will positively or negatively affect drivers’ enroute switching behavior and explored the causal effect by applying structural equation modeling. Then binary logit model was used to confirm whether latent variables and information scenarios will affect drivers’ enroute switching behavior. Empirical findings indicate that the latent variables of perceived value, usage attitude and compliance rate toward traffic information would positively enhance freeway drivers’ enroute switching rates, but switching barrier and congestion tolerability would largely impede them in the case of Taiwan. However, providing more detailed information on alternative routes can motivate drivers’ enroute switching behavior during traffic congestion.