Adaptive Route Choice Modeling in Uncertain Traffic Networks with Real-Time Information

The objective of the research is to study travelers' route choice behavior in uncertain traffic networks with real-time information. The research is motivated by two observations of the traffic system: 1) the system is inherently uncertain with random disturbances such as incidents, bad weather, and work zones, and therefore travel times are at most known with uncertainty; 2) traveler information is or will be available so that travelers could make travel decisions adaptive to the random disturbances to reduce negative effects of uncertainty. Two central research questions to be answered are: 1) Can we build and estimate an econometric model for travelers' en route updating of route choices? 2) Can such a model provide more realistic prediction of travelers' route choices than existing ones? The research will contribute to the state of the art by validating a novel adaptive route choice model on experimental data and providing understanding of route choice behavior in uncertain situations. The model is an integral component in evaluating the effectiveness of advanced traveler information systems (ATIS).