Modeling En-route Driver Route Choice Behavior Under Real-time Traffic Information

摘要

The purpose of this paper is to develop a process-oriented modeling approach for making possible a more proper description of en-route driver route choice behavior under real time traffic information. An en-route driver route choice behavior model that uses concepts from Decision Field Theory (DFT) and Bayesian Belief Network (BBN) is proposed. The preferences of routes which are directly accessible from the current position are obtained via BBN and DFT. A real-time planning algorithm for route choice processes is discussed in great detail. Using this algorithm, a driver develops his route dynamically until he reaches his destination. Critical factors that affect drivers' response to real time traffic information are quantitatively studied through interactive simulation and from the viewpoint of cognitive psychology. The simulation results show that the coiabination of DFT and BBN can effectively explain the driver's travel dynamics behavior.