Trajectory-Integrated Accessibility Analysis of Public Electric Vehicle Charging Stations

TL;DR

This paper introduces a new trajectory-integrated accessibility metric for public EV charging stations, assessing spatial and racial disparities in the San Francisco Bay Area using detailed individual trajectory data.

Contribution

It develops the TI-acs metric that incorporates travel trajectories, providing a more comprehensive assessment of EVCS accessibility beyond home-based measures.

Findings

Average daily access hours are 7.5 for L2 and 5.2 for DCFC stations.

Spatial disparities in accessibility are significant, with Gini indices of 0.38 and 0.44.

Racial disparities in accessibility are influenced by infrastructure and mobility patterns.

Abstract

Electric vehicle (EV) charging infrastructure is crucial for advancing EV adoption, managing charging loads, and ensuring equitable transportation electrification. However, there remains a notable gap in comprehensive accessibility metrics that integrate the mobility of the users. This study introduces a novel accessibility metric, termed Trajectory-Integrated Public EVCS Accessibility (TI-acs), and uses it to assess public electric vehicle charging station (EVCS) accessibility for approximately 6 million residents in the San Francisco Bay Area based on detailed individual trajectory data in one week. Unlike conventional home-based metrics, TI-acs incorporates the accessibility of EVCS along individuals' travel trajectories, bringing insights on more public charging contexts, including public charging near workplaces and charging during grid off-peak periods. As of June 2024, given the current public EVCS network, Bay Area residents have, on average, 7.5 hours and 5.2 hours of access per day during which their stay locations are within 1 km (i.e. 10-12 min walking) of a public L2 and DCFC charging port, respectively. Over the past decade, TI-acs has steadily increased from the rapid expansion of the EV market and charging infrastructure. However, spatial disparities remain significant, as reflected in Gini indices of 0.38 (L2) and 0.44 (DCFC) across census tracts. Additionally, our analysis reveals racial disparities in TI-acs, driven not only by variations in charging infrastructure near residential areas but also by differences in their mobility patterns.