Center for Traffic Simulation Studies

Dynamic traffic assignment (DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects still need improvement, especially in terms of its formulation and solution capabilities within the transportation environment impacted by advanced transportation management and information systems (ATMIS). We need to develop a set of DTA models to acknowledge the fact that the traffic network itself is probabilistic and uncertain and that different classes of travelers respond differently within this uncertain environment given different levels of traffic information. This paper aims to advance the state of the art of DTA modeling. Our proposed model captures the travelers' decision making among discrete choices in a probabilistic and uncertain environment in which both probabilistic travel times and random perception errors that are specific to individual travelers are considered. Travelers' route choices are assumed to be made with the objective of minimizing perceived disutilities at each time. These perceived disutilities depend on the distribution of the variable route travel times, the distribution of individual perception errors and the individual traveler's risk- taking nature at each time instant. We formulate the integrated DTA model through a variational inequality (VI) approach. We discuss the solution algorithm for the formulation and present experimental results to verify the correctness of solutions obtained.