Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TITS.2015.2506900 | IEEE Trans. Intelligent Transportation Systems |
Keywords | Field | DocType |
Charging stations,Routing,Roads,Stochastic processes,Electric vehicles,Vehicle dynamics | Energy management,Road networks,Charging station,Simulation,Stochastic process,Multi-agent system,Queueing theory,Mechanism design,Vehicle dynamics,Engineering | Journal |
Volume | Issue | ISSN |
17 | 5 | 1524-9050 |
Citations | PageRank | References |
10 | 0.67 | 17 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mathijs Weerdt | 1 | 411 | 41.00 |
| Sebastian Stein | 2 | 394 | 42.61 |
| Enrico H. Gerding | 3 | 759 | 77.42 |
| Valentin Robu | 4 | 948 | 70.44 |
| Nicholas R. Jennings | 5 | 19348 | 1564.35 |