Modeling Driver Psychological Deliberation During Dynamic Route Selection Processes

Dynamic route guidance (DRG) is an ITS application targeted to reduce the prolonged daily periods of severe congestion. The success of such system relies on its ability to disseminate reliable pieces of information to travelers in real time. The predictive accuracy of disseminated information requires a realistic understanding and representation of drivers´ behavior and more specifically their route choice decisions and processes. Accordingly, this research attempts to step out of the engineering borders to the psychological arena through adopting one of the most successful decision theories; decision field theory (DFT). The choice mechanism of DFT is based on the simulation of the evolution of decision-makers preferences through out the deliberation process reflecting a process-oriented modeling approach. This study presents a modeling framework for drivers´ decision making process based on the theoretical foundation of DFT. Three scenarios are discussed that vary in the level of traveler information presented to the driver, namely; no information, descriptive information (congestion states) and prescriptive information (specific guidance). Due to the highly intertwined elements of the theory and resulting model framework, an overly simplified application is used for illustration purposes