Collaborative Research: Stochastic and Dynamic Hyperpath Equilibrium Models

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This grant provides funding for the development of adaptive hyperpath equilibrium models for stochastic and dynamic transportation networks. These models will capture both individual driver behavior and the equilibration process that occurs across multiple drivers, and will represent the heterogeneity in driver risk preferences. A three-phase approach is proposed that addresses the behavioral foundations, the analytical formulation of the hyperpath equilibrium, and the application to a network pricing problem. In the first phase of the proposed research, an interactive web game will be used to study the nature of adaptive routing behavior under multiple route choice scenarios. The second phase builds on these results by developing a variational inequality formulation to represent the routing behavior. The final phase applies this model to develop adaptive congestion pricing strategies.If successful, the results of this research will result in a fundamentally new transportation planning tool that can assess the impacts of travel information tools. The fundamental idea is that travelers could use this information to change their driving behavior en route, perhaps avoiding congested roadways based on the information received. The research will model the system-level effects of many travelers receiving information and behaving in this way, keeping in mind differences in their travel purposes and risk tolerance. This model will also be used to evaluate how dynamic tolls should be adjusted in response to system disruptions. Accomplishing these goals will provide transportation planners with the tools to implement these technologies in a way which is most beneficial to the traveling public. This grant will provide the opportunity to expose multiple graduate students and under-graduate researchers to cutting edge research in large-scale network modeling, stochastic optimization and transportation economics. The PI?s will also interact with several local community organizations and educational programs to disseminate the results and insights to a wider audience.