United States Department of Transportation
i
Implications of Information Structure in Control of Urban Traffic Networks
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2020-09-01
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By Savla, Ketan
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Edition:Final report (8/1/2019–7/31/2020)
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Abstract:First, the authors consider optimal control of traffic flow over networks using a combination of variable speed limit, ramp meter, lane-changing, and routing control. While this problem has attracted significant attention, most of the prior work has been limited to centralized or open-loop control. The authors propose to develop the foundations for a framework to design closed-loop control under given information structures. The emphasis will be on computational tractability and characterization of performance gap with respect to centralized control. Second, the authors propose to study optimal information design to influence route choice decisions of drivers in dynamic environments. Specifically, the authors adopt the framework of algorithmic persuasion, under which the system planner can exploit information asymmetry about the knowledge of the real-time state of the network to release noisy information or recommend routes to the drivers in order to optimize social objective. The study of algorithmic persuasion in the context of routing games is very recent, and more so, the existing work implicitly assumes the drivers to evaluate the incentive compliant nature of the recommendations from the system planner only asymptotically, they do not consider externality from drivers who do not participate in persuasion, and assume static traffic flow models. In this project, the authors propose to address these shortcomings to develop foundations for algorithmic persuasion in routing games. The methodological contributions will be supplemented with case studies using traffic data from the Los Angeles area, and with simulation case studies in VISSIM.
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