We study drivers’ route choice behavior in a driving simulator with real-timetraffic information. A strategic route choice refers to a look-ahead decision taking intoaccount future diversion possibilities at downstream nodes based on real-timeinformation not yet available at the time of decision-making. A mixed Logit model withtwo latent classes, strategic and non-strategic route choice, is specified and estimated.The estimates of the latent class probabilities show that a significant portion of routechoice decisions are strategic and subjects can learn to make more strategic route choiceas they have more experience with the decision scenarios. Non-parametric tests also showthat a parallel driving task does not affect strategic thinking ability, which might becaused by the simplicity of the test network. The findings suggest that a realistic routechoice model with real-time information should consider both strategic and non-strategicbehavior, which potentially vary with the driver’s experience.
展开▼
