This study developed an approach to model network performance when its link capacities are subject to stochastic degradations, as in the form of day-to-day traffic incidents, which cause travel time variability. We postulate that drivers would select routes to lower their travel time variability, just as they would to lower their mean travel time. Over time, commuters learn the routes' travel time variability based on past experiences, factor such variability into their route choice considerations, and settle into a long-term equilibrium pattern. We characterize this route choice behavior in the face of uncertain travel times with the notion of probabilistic user equilibrium (PUB). This study then defined and formulated PUE with a reliability approach. We developed a pair of network analysis and design models to consider trip time reliability in a network with stochastic link capacities. The final result is nonlinear mathematical programs that relate the trip time reliability measure to travel demand and stochastic link capacity degradations. (Author/publisher) For the covering entry of this conference, please see ITRD abstract No. E208120.
Abstract