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Intention-Aware Routing of Electric Vehicles

handle: 10044/1/33196
This paper introduces a novel intention-aware routing system (IARS) for electric vehicles. This system enables vehicles to compute a routing policy that minimizes their expected journey time while considering the policies, or intentions , of other vehicles. Considering such intentions is critical for electric vehicles, which may need to recharge en route and face potentially significant queueing times if other vehicles choose the same charging stations. To address this, the computed routing policy takes into consideration predicted queueing times at the stations, which are derived from the current intentions of other electric vehicles. The efficacy of IARS is demonstrated through simulations using realistic settings based on real data from The Netherlands, including charging station locations, road networks, historical travel times, and journey origin–destination pairs. In these settings, IARS is compared with a number of state-of-the-art benchmark routing algorithms and achieves significantly lower average journey times. In some cases, IARS leads to an over 80% improvement in waiting times at charging stations and a more than 50% reduction in overall journey times.
- Delft University of Technology Netherlands
- Heriot-Watt University United Kingdom
- University of Southampton United Kingdom
- Heriot-Watt University United Kingdom
- Imperial College London United Kingdom
330, intelligent vehicles, Logistics & Transportation, 1507 Transportation And Freight Services, 0801 Artificial Intelligence And Image Processing, decision making, 0905 Civil Engineering, 004, 629, traffic control, multi-agent systems, vehicle routing, electric vehicles
330, intelligent vehicles, Logistics & Transportation, 1507 Transportation And Freight Services, 0801 Artificial Intelligence And Image Processing, decision making, 0905 Civil Engineering, 004, 629, traffic control, multi-agent systems, vehicle routing, electric vehicles
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).68 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% visibility views 7 download downloads 10 - 7views10downloads
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