Abstract
This paper presents a design of a relocation planner for electric vehicle sharing systems, which periodically redistributes vehicles over multiple stations for better serviceability. For the relocation vector, or target vehicle distribution given by a relocation strategy, the proposed planner builds two preference lists, one for vehicles in overflow stations and the other for underflow stations. Then, the matching procedure assigns each electric vehicle to a station in such a way to minimize the relocation distance and time by means of a modified stable marriage problem solver. The performance measurement is conducted by a prototype implementation on top of the previously developed analysis framework and real-life trip records in Jeju City area. The morning-focused relocation strategy can best benefit from the proposed relocation planner in terms of both the relocation distance and the number of moves, mainly due to symmetric traffic patterns in the morning and in the evening.
This research was supported by the MKE (The Ministry of Knowledge Economy), Republic of Korea, under IT/SW Creative research program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2012-(H0502-12-1002)).
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Lee, J., Kim, HJ., Park, GL. (2012). Relocation Action Planning in Electric Vehicle Sharing Systems. In: Sombattheera, C., Loi, N.K., Wankar, R., Quan, T. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2012. Lecture Notes in Computer Science(), vol 7694. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35455-7_5
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DOI: https://doi.org/10.1007/978-3-642-35455-7_5
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