A Real-Time Planning Algorithm for Route Choice Behavior and Processes

Abstract

The purpose of this paper is to develop a real-time planning algorithm for making possible a more proper description of drivers' route choice behavior and processes under real time traffic information in a traffic network. The algorithm uses concepts from Decision Field Theory (DFT) and Bayesian belief network (BBN). DFT is widely known in the field of mathematical psychology and is used to study drivers' multi-attribute cognition and decision process under real time traffic information. BBN is employed to infer updating of road condition under real time traffic information. Using this algorithm, a driver develops his route dynamically until he reaches his preferred destination. The preferences of routes which are directly accessible from the current position are obtained via BBN and DFT. Critical factors that affect drivers' response to real time traffic information are quantitatively studied through interactive simulation and from the viewpoint of cognitive psychology.