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Intention-aware routing of electric vehicles

Intention-aware routing of electric vehicles
Intention-aware routing of electric vehicles
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.
intelligent vehicles, decision making, electric vehicles, multi-agent systems, traffic control, vehicle routing
1524-9050
1472-1482
de Weerdt, M.
70709b56-041b-4dc2-ac60-46e93a33d31c
Stein, S.
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Gerding, E.
d9e92ee5-1a8c-4467-a689-8363e7743362
Robu, V.
ff014ae3-1a8b-46ac-8d87-5ad09181546b
Jennings, N.R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
de Weerdt, M.
70709b56-041b-4dc2-ac60-46e93a33d31c
Stein, S.
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Gerding, E.
d9e92ee5-1a8c-4467-a689-8363e7743362
Robu, V.
ff014ae3-1a8b-46ac-8d87-5ad09181546b
Jennings, N.R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

de Weerdt, M., Stein, S., Gerding, E., Robu, V. and Jennings, N.R. (2015) Intention-aware routing of electric vehicles. IEEE Transactions on Intelligent Transportation Systems, 17 (5), 1472-1482. (doi:10.1109/TITS.2015.2506900).

Record type: Article

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.

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07365482.pdf - Accepted Manuscript
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More information

Accepted/In Press date: 30 November 2015
Published date: 24 December 2015
Keywords: intelligent vehicles, decision making, electric vehicles, multi-agent systems, traffic control, vehicle routing
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 385385
URI: https://eprints.soton.ac.uk/id/eprint/385385
ISSN: 1524-9050
PURE UUID: 326d2e7f-899b-4bfe-a05c-d734a337b7fc

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Date deposited: 29 Dec 2015 14:34
Last modified: 17 Jul 2017 19:56

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Contributors

Author: M. de Weerdt
Author: S. Stein
Author: E. Gerding
Author: V. Robu
Author: N.R. Jennings

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