In this paper, we study an online charge scheduling strategy for fleets of autonomous-mobility-on-demand electric vehicles (AMoD EVs). We consider the case where vehicles complete trips and then enter a between-ride state throughout the day, with their information becoming available to the fleet operator in an online fashion. In the between-ride state, the vehicles must be scheduled for charging and then routed to their next passenger pick-up locations. Additionally, due to the unknown daily sequences of ride requests, the problem cannot be solved by any offline approach. As such, we study an online welfare maximization heuristic based on primal-dual methods that allocates limited fleet charging resources and rebalances the vehicles while avoiding congestion at charging facilities and pick-up locations. We discuss a competitive ratio result comparing the performance of our online solution to the clairvoyant offline solution and provide numerical results highlighting the performance of our heuristic.
Online Charge Scheduling for Electric Vehicles in Autonomous Mobility on Demand Fleets
01.10.2019
807782 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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