Document Type

Thesis

Date of Award

6-2025

School/College

College of Science, Engineering, and Technology (COSET)

Degree Name

MS in Transportation Planning & Management

Committee Chairperson

Dr. Mehdi Azimi

Committee Member 1

Dr. Yi Qi

Committee Member 2

Dr. Gwendolyn Goodwin

Committee Member 3

Dr. Shahryar Darayan

Keywords

Electric Vehicle Charging Stations, Analytic Hierarchy Process (AHP), Infrastructure Planning, Multi-Criteria Decision-Making, Transportation Systems.

Abstract

The growing adoption of electric vehicles (EVs) requires metropolitan areas to strategically plan the placement of charging infrastructure to support accessibility, efficiency, and sustainability. This study investigates key determinants for the optimal siting of EV charging stations, using Houston, Texas, as a case study. Through a comprehensive literature review and expert consultation, eight critical criteria were identified: land use type, population density, median income level of residents in the area, vehicle ownership rate in the area, young and middle-aged residents share in the area, flood risk, traffic density and proximity to major roads, and educational attainment of the residents in the area. To evaluate the relative importance of these criteria, the study employed the Analytic Hierarchy Process (AHP), analyzing pairwise comparison responses from 39 transportation professionals. Results indicated that infrastructure-related and accessibility factor (traffic density and proximity to major roads) was rated most important, followed by land use type and vehicle ownership rate in the area. Environmental risk (flooding) held moderate importance, while demographic and socioeconomic factors such as population density, education attainment of residents in the area, median income level of residents in the area, and the share of young and middle-aged residents in the area were ranked lower. The consistency ratio of 0.014 confirmed the reliability of expert responses. The findings highlight the value of data-driven, multi-criteria approaches in EV infrastructure planning, and the study offers actionable insights for urban planners and policymakers.

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