Print Email Facebook Twitter Intention-Aware Routing to Minimise Delays at Electric Vehicle Charging Stations Title Intention-Aware Routing to Minimise Delays at Electric Vehicle Charging Stations Author De Weerdt, M.M. Gerding, E.H. Stein, S. Robu, V. Jennings, N.R. Faculty Electrical Engineering, Mathematics and Computer Science Department Software and Computer Technology Date 2013-04-22 Abstract En-route charging stations allow electric vehicles to greatly extend their range. However, as a full charge takes a considerable amount of time, there may be significant waiting times at peak hours. To address this problem, we propose a novel navigation system, which communicates its intentions (i.e., routing policies) to other drivers. Using these intentions, our system accurately predicts congestion at charging stations and suggests the most efficient route to its user. We achieve this by extending existing time-dependent stochastic routing algorithms to include the battery's state of charge and charging stations. Furthermore, we describe a novel technique for combining historical information with agent intentions to predict the queues at charging stations. Through simulations we show that our system leads to a significant increase in utility compared to existing approaches that do not explicitly model waiting times or use intentions, in some cases reducing waiting times by over 80% and achieving near-optimal overall journey times. Subject multi-agent planningcomputational sustainabilitycoordination and collaborationmulti-agent systemsenergyshortest-path planning To reference this document use: http://resolver.tudelft.nl/uuid:492b1dbd-e735-4ac8-a025-bae4a3a42d5e Publisher AAAI Press Part of collection Institutional Repository Document type conference paper Rights (c) 2013 De Weerdt, M.M.Gerding, E.H.Stein, S.Robu, V.Jennings, N.R. Files PDF deweerdt.pdf 256.53 KB Close viewer /islandora/object/uuid:492b1dbd-e735-4ac8-a025-bae4a3a42d5e/datastream/OBJ/view