Xu, Fuguo (Dalian University of Technology), Shen, Tielong (Sophia University), Kuboyama, Tatsuya (Chiba University)

Receding Horizon-Type Mean Field Control-Based Speed Optimization for Large-Population Connected and Automated Vehicles

Scheduled for presentation during the Regular Session "Vehicle autonomy and connectivity" (TuA2), Tuesday, June 17, 2025, 10:30−10:50, Jos

AAC 2025 11th IFAC International Symposium on Advances in Automotive Control, June 15-18, 2025, Eindhoven, Netherlands

This information is tentative and subject to change. Compiled on June 1, 2025

Abstract

With the highly increasing penetration of connected and automated vehicles (CAVs), fuel consumption reduction and traffic utilization improvement can be achieved further. This paper explores the potential to reduce the whole fuel consumption for a large population of connected and automated HEVs. To avoid the computation burden of a large population of CAVs, a novel decentralized control scheme is designed by employing the mean field game (MFG) theory. The receding horizon sense is introduced to MFG to avoid the open-loop prediction error of velocity distribution within the optimization horizon. Simulations are conducted to show the effectiveness of the proposed strategy.