Background:

This study measures spatial accessibility to electric vehicle (EV) charging stations in Vancouver using a service area analysis. By generating travel-time polygons from dissemination area (DA) centroids, we evaluate how many charging ports are reachable within 15-minute drive times. Accessibility is assessed during different times of day, accounting for traffic variations using ArcGIS Online’s network dataset. The results help identify underserved areas with limited EV infrastructure and guide future investments in equitable, sustainable transportation planning across the city as EV adoption continues to grow.

Objectives:

Assess Spatial Accessibility

Incorporate Temporal Variation

Support Infrastructure Planning

Methods:

To measure access to electric vehicle (EV) charging stations in Vancouver, a four-step process was used. First, 15-minute driving zones were generated using ArcGIS Pro for two groups of neighborhood points, across different departure times. Second, the two batches were merged to create a complete map for each time. Third, EV charging stations were counted within each zone using a spatial join. Finally, the results were cleaned in R by extracting neighborhood IDs and matching them with the number of reachable stations. This method helped identify areas with strong EV access and those that may need improved infrastructure.

Results:

Figure 1 illustrates the distribution of electric vehicle (EV) charging stations by type across Vancouver. Most Level 2 and Level 3 stations are concentrated in the downtown core and central neighbourhoods, while southern and eastern areas have noticeably fewer options. This uneven distribution creates spatial disparities in access to charging infrastructure.

Figure 2 presents composite maps showing how many stations are reachable within a 15-minute drive at different times of day. Accessibility is greatest during off-peak hours, such as 12 AM and 9 PM, when less congestion allows for broader service coverage. In contrast, during peak periods—especially 5 PM and 6 PM—traffic significantly reduces the number of accessible stations, particularly in the city’s outer regions. Even at 7 AM and 12 PM, minor reductions in reachability are observed. These patterns highlight how both geography and traffic congestion jointly shape access to EV charging, potentially reinforcing inequities for residents outside the urban core.

Figure 1 – Map of EV Station Locations by Charging Type
Figure 2 – Composite Map of EV Stations Accessible Within a 15 Minute Drive Time

Limitations:

While this study provides valuable insight into spatial and temporal access to EV charging stations, several limitations should be noted. The analysis only captures accessibility by private vehicle and does not account for pedestrian or multimodal access, which may be relevant in denser urban areas. Second, station availability was assumed to be constant; real-time occupancy, maintenance issues, or charging speed differences were not considered, potentially overestimating practical accessibility. Additionally, while traffic data was integrated, it reflects average conditions rather than real-time fluctuations or seasonal variability. The data cleaning and spatial processing steps were also conducted manually, which is time-intensive and prone to human error. An automated workflow using the ArcGIS Python API and batch processing was developed, but could not be fully implemented in this version of the project due to technical constraints. Future work aims to streamline and automate this pipeline to improve reproducibility, efficiency, and scalability across time periods and geographies.

Acknowledgements:

I would like to sincerely thank Dr. Jinhyung Lee and Henry Shaver for their invaluable support, guidance, and encouragement throughout this research project. Their expertise and mentorship made this work possible and greatly enriched my learning experience. I’m incredibly grateful for the opportunity to contribute to this research and excited to continue working with them on my undergraduate thesis in the 25/26 school year.

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