A vehicle coordination and charge scheduling algorithm for electric Autonomous Mobility-on-Demand Systems

Felix Boewing, Maximilian Schiffer, Mauro Salazar, Marco Pavone

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)

Samenvatting

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.
Originele taal-2Engels
Titel2020 American Control Conference, ACC 2020
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's248-255
Aantal pagina's8
ISBN van elektronische versie9781538682661
DOI's
StatusGepubliceerd - jul 2020
Evenement2020 American Control Conference (ACC2020) - Denver, Verenigde Staten van Amerika
Duur: 1 jul 20203 jul 2020
http://acc2020.a2c2.org/

Congres

Congres2020 American Control Conference (ACC2020)
Verkorte titelACC2020
LandVerenigde Staten van Amerika
StadDenver
Periode1/07/203/07/20
Internet adres

Bibliografische nota

Publisher Copyright:
© 2020 AACC.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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