Utilizing Game Theory to Optimize In-motion Wireless Charging Service Efficiency for Electric Vehicles

Abstract

Charger lanes, which are road segments equipped with in-motion wireless chargers, are expected to keep Electric Vehicles (EVs) continuously driving without recharging downtime. To maximize the service efficiency of the in-motion wireless chargers, we must properly coordinate the traffic of the EVs to avoid the generation of congestion at the charger lanes and on the road segments to them. In this article, we propose WPT-Opt, a game-theoretic approach for optimizing in-motion wireless charging efficiency, minimizing EVs' driving time to the charger, and avoiding traffic congestion at the charger lanes to fulfill this task. We studied a metropolitan-scale dataset of public transportation EVs and observed the EVs' spatial and temporal preference in selecting chargers, competition for chargers during busy charging times, the relationship between vehicle density and driving velocity on a road segment, the normal distribution of travel time of road segments, and the fact that vehicles have similar frequently driven trajectories. Based on the observations, a central controller estimates the vehicle density of the road segments by measuring the vehicles' trajectory travel time, the friendship among the vehicles, and the vehicles' routing choice given the presence of charger lanes. Then, we formulate a non-cooperative Stackelberg game between all the EVs and the central controller, in which each EV aims at minimizing its charging time cost to its selected target charger, while the central controller tries to maximally avoid the generation of congestion on the way through the in-motion wireless chargers. Our trace-driven experiments on SUMO demonstrate that WPT-Opt can maximally reduce the average charging time cost of the EVs by approximately 200% during different hours of a day.