Road Pricing Design Based on Game Theory and Multi-agent Consensus |
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Authors: | Nan Xiao Xuehe Wang Lihua Xie Tichakorn Wongpiromsarn Emilio Frazzoli Daniela Rus |
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Affiliation: | 1. Singapore-MIT Alliance for Research and Technology Centre, Singapore 138602, Singapore;2. EXQUISITUS, Centre for ECity, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore;3. Ministry of Science and Technology, Bangkok 10400, Thailand;4. Massachusetts Institute of Technology, Cambridge MA 02139, USA |
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Abstract: | Consensus theory and noncooperative game theory respectively deal with cooperative and noncooperative interactions among multiple players/agents. They provide a natural framework for road pricing design, since each motorist may myopically optimize his or her own utility as a function of road price and collectively communicate with his or her friends and neighbors on traffic situation at the same time. This paper considers the road pricing design by using game theory and consensus theory. For the case where a system supervisor broadcasts information on the overall system to each agent, we present a variant of standard fictitious play called average strategy fictitious play (ASFP) for large-scale repeated congestion games. Only a weighted running average of all other players' actions is assumed to be available to each player. The ASFP reduces the burden of both information gathering and information processing for each player. Compared to the joint strategy fictitious play (JSFP) studied in the literature, the updating process of utility functions for each player is avoided. We prove that there exists at least one pure strategy Nash equilibrium for the congestion game under investigation, and the players' actions generated by the ASFP with inertia (players' reluctance to change their previous actions) converge to a Nash equilibrium almost surely. For the case without broadcasting, a consensus protocol is introduced for individual agents to estimate the percentage of players choosing each resource, and the convergence property of players' action profile is still ensured. The results are applied to road pricing design to achieve socially local optimal trip timing. Simulation results are provided based on the real traffic data for the Singapore case study. |
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Keywords: | Average strategy fictitious play (ASFP) game theory multi-agent consensus road pricing |
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