Modelling an electricity price and journey time trade-off routing decision for electric vehicles

Bachelor thesis (2021)

Authors

J.L.K. van Loon Electrical Engineering, Mathematics and Computer Science

Contributors

Valentin Robu Algorithmics - EEMCS (supervisor 1)
C. Lofi Web Information Systems - EEMCS (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2021 Joaquin van Loon
Vehicle routing Traffic control Electric vehicles Decision making Mult-agent systems
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Published Date

01-07-2021

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

This paper introduces an electricity price extension to the intention-aware routing system (IARS) for electric vehicles (EV). The existing intention-aware routing system is used to route electric vehicles who require to charge en-route through a road network. To achieve the objective of minimising the average journey time, the intentions of EVs and waiting times at charging stations are com- municated. Instead of only minimizing travel time, the model extension presented in this paper makes it possible to express a decision trade-off between price and time. A vehicle computes its routing policy such that the combined utility of price and time is as high as possible. In this paper the performance of IARS with a price extension is compared to a greedy maximising algorithm (MAX) in several settings. The increase in utility by using IARS depends on the population of electric vehicles. However, in most experiments conducted in this research IARS achieves a significantly higher average utility.