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Paper WeAT15.7

Ning, Yuqiang (University of Florida), Du, Lili (University of Florida)

A Dynamic Coordinated Joint Routing and En-Route Charging Mechanism for Traffic Congestion Mitigation: Game-Theoretic Modeling and Distributed Optimization

Scheduled for presentation during the Poster Session "Vehicle routing" (WeAT15), Wednesday, September 25, 2024, 10:30−12:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 7, 2024

Keywords Travel Information, Travel Guidance, and Travel Demand Management, Network Modeling

Abstract

As electric vehicles (EVs) grow in popularity, new challenges emerge regarding congestion at charging stations and on roads. Real-time traffic and charging information enables informed routing/charging decisions, but independent selfish reactions can exacerbate congestion due to the flash crowd effect. This study develops a dynamic coordinated joint routing and en-route charging mechanism (DcRC) to provide guidance for EVs and ICE vehicles, reducing road and charging station congestions. Considering traffic flow and charging queueing dynamics, DcRC is formulated as a mixed strategy congestion game with an equivalent mathematical model generating equilibrium routing and charging decisions (ERCD) to mitigate flash crowd effects without violating vehicle self-interests. A distributed ADMM-aided Branch-and-Bound (DAB) algorithm efficiently solves DcRC with hundreds of participants. Numerical experiments validate DcRC's effectiveness in reducing congestion/system costs and DAB's efficiency in supporting real-time navigation services.

 

 

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