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Title: A Vehicle Coordination and Charge Scheduling Algorithm for Electric Autonomous Mobility-on-Demand Systems
This paper presents an algorithmic framework to optimize the operation of an Autonomous Mobility-on-Demand system whereby a centrally controlled fleet of electric self-driving vehicles provides on-demand mobility. In particular, we first present a mixed-integer linear program that captures the joint vehicle coordination and charge scheduling problem, accounting for the battery level of the single vehicles and the energy availability in the power grid. Second, we devise a heuristic algorithm to compute near-optimal solutions in polynomial time. Finally, we apply our algorithm to realistic case studies for Newport Beach, CA. Our results validate the near optimality of our method with respect to the global optimum, whilst suggesting that through vehicle-to-grid operation we can enable a 100% penetration of renewable energy sources and still provide a high-quality mobility service.  more » « less
Award ID(s):
1837135
NSF-PAR ID:
10211556
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
2020 American Control Conference (ACC)
Page Range / eLocation ID:
248 to 255
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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