Please use this identifier to cite or link to this item: https://doi.org/10.1109/TASE.2009.2028577
DC FieldValue
dc.titleA collaborative multiagent taxi-dispatch system
dc.contributor.authorSeow, K.T.
dc.contributor.authorDang, N.H.
dc.contributor.authorLee, D.-H.
dc.date.accessioned2014-04-23T07:07:04Z
dc.date.available2014-04-23T07:07:04Z
dc.date.issued2010-07
dc.identifier.citationSeow, K.T., Dang, N.H., Lee, D.-H. (2010-07). A collaborative multiagent taxi-dispatch system. IEEE Transactions on Automation Science and Engineering 7 (3) : 607-616. ScholarBank@NUS Repository. https://doi.org/10.1109/TASE.2009.2028577
dc.identifier.issn15455955
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/50657
dc.description.abstractThis paper presents a novel multiagent approach to automating taxi dispatch that services current bookings in a distributed fashion. The existing system in use by a taxi operator in Singapore and elsewhere, attempts to increase customer satisfaction locally, by sequentially dispatching nearby taxis to service customers. The proposed dispatch system attempts to increase customer satisfaction more globally, by concurrently dispatching multiple taxis to the same number of customers in the same geographical region, and vis - vis human driver satisfaction. To realize the system, a multiagent architecture is proposed, populated with software collaborative agents that can actively negotiate on behalf of taxi drivers in groups of size N for available customer bookings. Theoretically, an analysis of the boundary and optimal multiagent taxi-dispatch situations is presented along with a discussion of their implications. Experimentally, the operational efficiency of the existing and proposed dispatch systems was evaluated through computer simulations. The empirical results, obtained for a 1000-strong taxi fleet over a discrete range of N, show that the proposed system can dispatch taxis with reduction in customer waiting and empty taxi cruising times of up to 33.1% and 26.3%, respectively; and up to 41.8% and 41.2% reduction when a simple negotiation speedup heuristic was applied. © 2010 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TASE.2009.2028577
dc.sourceScopus
dc.subjectAutomated software agents
dc.subjectintelligent paratransit transportation
dc.subjectservice automation
dc.subjecttaxi dispatch
dc.typeArticle
dc.contributor.departmentCIVIL ENGINEERING
dc.description.doi10.1109/TASE.2009.2028577
dc.description.sourcetitleIEEE Transactions on Automation Science and Engineering
dc.description.volume7
dc.description.issue3
dc.description.page607-616
dc.identifier.isiut000281938500017
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