Abstract
The shift towards electrical transportation system has the promise to decrease greenhouse gas emissions and reinforce sustainability. With the expected rise in electric vehicle (EV) usage in recent years, it becomes critical to develop a charging station infrastructure to ensure the drivers comfortability and optimal performance for EVs. This research recommends that EV drivers need to consider using the combination of the BWM and TOPSIS to select the most appropriate nearby charging stations based on their personal preferences and specific situations. The principal goal of the study is to improve the process of choosing charging stations based on the drivers' preferences. By comparing criteria weights and evaluating scores for all nearby charging stations to the drivers. This approach endeavors to offer a personalized selection process by integrating both the prevailing data and the user's unique preferences.
| Original language | English |
|---|---|
| Pages (from-to) | 472-479 |
| Number of pages | 8 |
| Journal | Transportation Research Procedia |
| Volume | 84 |
| DOIs | |
| State | Published - 2025 |
| Event | 1st Internation Conference on Smart Mobility and Logistics Ecosystems, SMiLE 2024 - Dhahran, Saudi Arabia Duration: 17 Sep 2024 → 19 Sep 2024 |
Bibliographical note
Publisher Copyright:© 2024 The Authors. Published by ELSEVIER B.V.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy -
SDG 13 Climate Action
Keywords
- TOPSIS
- best-worst-method
- charging infrastructure
- ranking charging stations
ASJC Scopus subject areas
- Transportation
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