A network-sensitive integrated travel model for simulating impacts of real-time traveler information

Real-time information systems are being used widely around the world to mitigate the adverse impacts of congestion and events that contribute to network delay. It is important that transportation modeling tools be able to accurately model the impacts of real-time information provision. Such planning tools allow the simulation of the impacts of various real-time information systems, and the design of traveler information systems that can minimize impacts of congestion and network disruptions. Such modeling tools would also be helpful in planning emergency response services as well as evacuation scenarios in the event of a natural disaster. Transportation modeling tools currently in use are quite limited in their ability to model the impacts of real-time information provision on travel demand and route choices. This dissertation research focuses on enhancing a previously developed integrated transportation modeling system dubbed SimTRAVEL (Simulator of Transport, Routes, Activities, Vehicles, Emissions, and Land) to incorporate capabilities that allow the simulation of the impacts of real-time traveler information systems on activity-travel demand. The first enhancement made to the SimTRAVEL framework involves the ability to reflect the effects of providing information on prevailing (as opposed to historical) network conditions on activity-travel behavior choices. In addition, the model system is enhanced to accommodate multiple user information classes (pre-trip and enroute) simultaneously. The second major contribution involves advancing the methodological framework to model enroute decision making processes where a traveler may alter his or her travel choices (such as destination choice) while enroute to an intended destination. Travelers who are provided up-to-date network information may choose to alter their destination in response to congested conditions, or completely abandon and reschedule an activity that offers some degree of flexibility. In this dissertation research, the model framework is developed and an illustrative demonstration of the capabilities of the enhanced model system is provided using a subregion of the Greater Phoenix metropolitan area in Arizona. The results show that the model is able to simulate adjustments in travel choices that may result from the introduction of real-time traveler information. The efficacy of the integrated travel model system is also demonstrated through the application of the enhanced model system to evaluate transportation policy scenarios.