Intention-Aware Routing to Minimise Delays at Electric Vehicle Charging Stations
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 83-88.
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.
@inproceedings{ijcai2013p24,
title = {Intention-Aware Routing to Minimise Delays at Electric Vehicle Charging Stations},
author = {de Weerdt, Mathijs and Gerding, Enrico H. and Stein, Sebastian and Robu, Valentin and Jennings, Nicholas R.},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {83--88},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/24},
}
TY - CPAPER TI - Intention-Aware Routing to Minimise Delays at Electric Vehicle Charging Stations AU - de Weerdt, Mathijs AU - Gerding, Enrico H. AU - Stein, Sebastian AU - Robu, Valentin AU - Jennings, Nicholas R. T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 83 EP - 88 UR - https://ijcai.org/proceedings/2013/24 ER -Copied
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