An approach for mapping an electric vehicle (EV) driver’s travel time constraints and risk-taking behavior to real-time routing in a probabilistic, time-dependent (or stochastic) network is proposed in this paper. The proposed approach is based on a heuristic algorithm that finds the shortest path according to the driver’s preferences. Accounting for en-route delays and alternate routes, the EV routing problem in stochastic networks is shown to exhibit other than the First-In-First-Out (FIFO) property; i.e., the traveling time for those who depart earlier may not reach sooner of those who depart later or wait en-route in the charging stations. The proposed approach provides EV drivers the option to manage their trip and reach the destination on time, while by taking advantage of the non-FIFO characteristics of the traffic network, charge their cars en-route. The proposed routing algorithm is tested on a given stochastic transportation network. The best routes based on the driver’s preferences are identified while accounting for the best-planned delays at the charging stations or en-route.
Routing of Electric Vehicles in a Stochastic Network with Non-recurrent Incidents
08.04.2020
American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS); Vol 67 No 1 (2020); 25-35 ; 2313-4402 ; 2313-4410
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC: | 629 |
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