Traffic modelling framework for electric vehicles

Abstract

This article reviews and improves a recently proposed model of road network dynamics. The model is also adapted and generalised to represent the patterns of battery consumption of electric vehicles travelling in the road network. Simulations from the mobility simulator SUMO are given to support and to illustrate the efficacy of the proposed approach. Applications relevant in the field of electric vehicles, such as optimal routing and traffic load control, are provided to illustrate how the proposed model can be used to address typical problems arising in contemporary road network planning and electric vehicle mobility.

Keywords:

• road network model
• Markov chain
• electric vehicles
• large-scale control and optimisation

Acknowledgements

The authors would like to thank the (anonymous) reviewers whose remarks contributed to improve the quality and the clarity of the final version of this article. They also thank Audrey La Louze and Faustine Richaud both from Université de Provence in Marseille for helpful discussions that helped writing the section about alternative flow conservation assumptions. Stephen Kirkland is supported in part by the Science Foundation Ireland under Grant No. SFI/07/SK/I1216b. Robert Shorten and Emanuele Crisostomi are supported in part by Science Foundation Ireland under grant number PI Award 07/IN.1/1901. Arieh Schlote is supported in part by HEA grant PRTLI5 TGI.

Notes

Notes

1. Source: Professor D. Banister (Oxford); Public Lecture; TU-Berlin; 29 September 2011.

2. Source: Professor D. Banister (Oxford); Public Lecture; TU-Berlin; 29 September 2011.

3. SUMO is an open source road traffic simulation package that was developed at the Institute of Transportation Systems at the German Aerospace Center, and is licensed under the GPL. Specifically, SUMO is used to generate data to build our Markov chain, to validate the outcomes of our modelling approach and to illustrate other merits of the Markovian approach.