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Real-time schedule optimization in shared electric vehicle fleets

 
: Kötter, Falko; Ostermann, Julien

:
Volltext urn:nbn:de:0011-n-4022843 (381 KByte PDF)
MD5 Fingerprint: a5642310536bdc972314692d4547e323
Erstellt am: 14.11.2018


Helfert, Markus (Ed.) ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
VEHITS 2016, International Conference on Vehicle Technology and Intelligent Transport Systems. Proceedings : Rome, Italy, April 23-24, 2016
Setúbal: SciTePress, 2016
ISBN: 978-989-758-185-4
S.253-263
International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS) <2, 2016, Rome>
Bundesministerium für Wirtschaft und Technologie BMWi
IKT für Elektromobilität; 01ME12105; Shared E-Fleet
Intelligenter Betrieb von gemeinsam genutzten Elektrofahrzeugflotten
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAO ()

Abstract
Use of electric vehicles in corporate carsharing has become a promising option. However, to make the use of electric vehicles economically feasible, a high degree of utilization is necessary. In the Shared E-Fleet project, solutions for shared car fleets are being researched, increasing utilization by sharing cars among different companies. In this work, we present a process and algorithms for real-time vehicle schedule optimization, aiming to minimize manual scheduling work, to optimize the schedule towards a goal function (e.g. minimizing emissions) and to compensate disruptions in real-time. We evaluate the approach using synthetic data and model trials, showing that schedule optimization increases utilization as well as quality-of-service.

: http://publica.fraunhofer.de/dokumente/N-402284.html