Towards Online Electric Vehicle Scheduling for Mobility-On-Demand Schemes

We study a setting where electric vehicles (EVs) can be hired to drive from pick-up to drop-off stations in a mobility-on-demand (MoD) scheme. Each point in the MoD scheme is equipped with battery charge facility to cope with the EVs' limited range. Customer-agents announce their trip requests over time, and the goal for the system is to maximize the number of them that are serviced. In this vein, we propose two scheduling algorithms for assigning EVs to agents. The first one is efficient for short term reservations, while the second for both short and long term ones. While evaluating our algorithms in a setting using real data on MoD locations, we observe that the long term algorithm achieves on average 2.08% higher customer satisfaction and 2.87% higher vehicle utilization compared to the short term one for 120 trip requests, but with 17.8% higher execution time. Moreover, we propose a software package that allows for efficient management of a MoD scheme from the side of a company, and easy trip requests for customers.