Abstract
Achieving carbon-neutral transportation is the ultimate goal of the ongoing joint efforts of governments, policy-makers, and the transportation research community. Electrification of smart cities is a very important step towards the above objective; therefore, accelerating the adoption and widening the use of Electric Vehicles (EVs) are required. However, to achieve the full potential of EVs, ground-breaking detour computation and charging station selection schemes are needed. To this end, this paper developed a new scheme that finds the most suitable detour/route for an EV whenever an unexpected event occurs on the road. This scheme is based on A* and uses an original, Simple-Additive-Weighting (SAW)-based, charging station selection method. The performance evaluation carried out using the open-source traffic simulation platform SUMO under a grid map, as well as a real road network map highlighted that our scheme ensured more than 99% of EVs will reach their destination within a reasonable time even if a battery recharge is needed. This is a significant improvement compared to the baseline scheme that uses the A* only.
| Original language | English |
|---|---|
| Article number | 803 |
| Number of pages | 21 |
| Journal | Electronics |
| Volume | 11 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 4 Mar 2022 |
| Externally published | Yes |
Bibliographical note
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Keywords
- electric vehicles
- detour
- route computation
- smart cities
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Hardware and Architecture
- Computer Networks and Communications
