Considering dynamic knowledge updating in bounded rationality–based route choice modeling

Abstract

To study the effect of en-route information on driver's route choice behavior, a dynamic route choice modeling approach is proposed, which takes the driver's knowledge updating process into consideration. A Bayesian network is developed to describe the en-route travel time updating process. Within the framework of the cumulative prospect theory, a choice model is conducted to analyze the driver's route choice behavior at each decision node. A numerical example is carried out to illustrate the application of the dynamic route choice modeling approach. The result demonstrates that the route choice behavior considering en-route information is a dynamic process. The traditional route choice model based on cumulative prospect theory without considering en-route information is also employed as a reference in the experiment. From the comparison, the dynamic route choice modeling approach in which a driver's knowledge of making en-route decisions is taken into account has a better goodness of fit. A stated preference survey is carried out to investigate drivers' route choice behaviors under different traffic scenario. The result indicates that the proposed approach could provide a more accurate description to driver's route choice behavior under the conditions of uncertainty.

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