Modeling, Relocation, and Real-Time Inventory Control of One-Way Electric Cars Sharing Systems in a Stochastic Petri Nets Framework

In recent years, one-way Electric Car sharing (ECs) systems have been introduced in many cities. One-way trips, as well as battery range issues, directly influence the quality and dynamics of such systems. Due to the demand and supply imbalance at stations, the ECs operators are faced with crucial operational challenges to reduce the relocation costs and increase the number of users. An agent-based relocation strategy based on real-time inventory control within the framework of generalized stochastic Petri Nets (PN) and a discrete event simulation has been proposed in this paper. Furthermore, an associated system performance evaluation was also developed. This model further assesses the effects of system characteristics such as the battery charging level availability threshold on the behavior and dynamics of the system. Moreover, the developed model and simulation show the potential of using PN models to predict critical situations, analyze relocation strategy efficiency, and improve system performance. Results from the simulation indicate that the overall relocation trips are reduced by estimating the time to launch the relocation process, as well as the conflicts between agents (controlling the assignment of agents among stations) during the balancing process are efficiently resolved. The proposed model and simulation algorithm have been applied to the BlueSG network in downtown Singapore.