PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
A Preliminary Study on Anticipatory Stigmergy for Traffic Management
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
Hi-index | 0.00 |
This paper describes an evolutionary game-theoretic learning model for dynamic congestion pricing in urban road networks, taking into account route choice stochasticity and reliability considerations, and the heterogeneity of users, in terms of their value of travel time and real-time information acquisition. The learning model represents the dynamic adjustments of users to travel cost changes which may take place in the day-to-day as well as the within-day timescales. The implementation into a simplified and a real urban road network signifies the important implications of modeling the dynamic and stochastic learning components of users' behavior for accommodating the efficient deployment of congestion pricing schemes.