Model Route-Swapping Behavior Regularities:Based On Laboratory Experiments

Commuters may switch from a route to another in response to feedback information regarding actual(and foregone)travel cost for the last few days.To better capture typical individual response modes under strategic uncertainty in congestible traffic networks,we conducted laboratory experiments in different senarios.Equilibrium solution seems to perform well in accounting for the aggregate route choices,whereas the high degree of volatility persists until the end of the games.Behavioral learning models seem to fail to capture the switching frequency distribution among the players.With switching rate between two consecutive time steps as the measure of response modes,four typical response modes are captured,that is,highly responsive players(holding Direct-response-like and Contrary-response-like patterns)and Highly-risk-averse players,the Status-quo-maintenance category players.An indepth analysis of potential behavioral bases of each type was discussed.Also,we observed the asyemmesy in inertia tendency and route preference.According to these observations,a deterministic day-to-day model was proposed and proved to have a unique equilibrium state and a stable evolution process.The results of model calibration indicate that the model is able to reproduce well the experimental observations,including equilibrium network flows and the switching rates among travelers.This work would contribute to better understanding of actual commuters’ route-choice behavior and the day-to-day evolution of network flows.