Online Charge Scheduling for Electric Vehicles in Autonomous Mobility on Demand Fleets
Abstract
In this paper, we study an online charge scheduling strategy for fleets of autonomous-mobility-on-demand electric vechicles (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.
Keywords
Cite
@article{arxiv.1907.01071,
title = {Online Charge Scheduling for Electric Vehicles in Autonomous Mobility on Demand Fleets},
author = {Nathaniel Tucker and Berkay Turan and Mahnoosh Alizadeh},
journal= {arXiv preprint arXiv:1907.01071},
year = {2019}
}
Comments
9 pages, 3 figures, Accepted to ITSC 2019, Auckland, NZ