Rebalancing and Charging Scheduling With Price Incentives for Car Sharing Systems

Abstract

This paper studies the joint problem of optimal pricing, charging scheduling and rebalancing for one-way car sharing systems. Firstly, a price driven customers travel mechanism is given which represents the customers ride demand as a linear function of the ride price. Then, a joint framework ensuring load balance and profit maximization of the system is introduced, in which the migration of vehicles and customers in the system is captured by fluid models, while the charging procedure of electric vehicles in the charging stations is described by multi-server queues. The well-posedness and equilibrium of the fluid model are analyzed, which yields the minimum fleet size needed. Next, a rebalancing method is derived to maximize the operating income while the stations operate at an equilibrium state, i.e., vehicles available and no waiting customers. To make the system better adapt to the changing customers demand in highly dynamic environments, a real-time rebalancing policy is developed by introducing a customer arrival predicting scheme based on exponential smoothing. Numerical experiments and case studies in Chengdu show that the proposed method can significantly improve the quality of service and rebalancing performance.