About the project
E-bike crashes are rising fast. A study by the University of California, San Francisco found that hospitalizations from e-bike accidents grew 99% a year from 2017 to 2022, yet there is very little data on where these crashes happen and why. My research asks: how do road properties influence the risk of e-bike crashes in California and Sonoma County?
I pulled e-bike crashes from the California Crash Reporting System (CCRS), which covers crashes reported to the California Highway Patrol from 2016 to 2026, and matched them to road data from OpenStreetMap, such as speed limits and lane counts. Here’s what I found:
- Faster roads see more crashes. Statewide, 1,586 crashes happened on roads with a speed limit of 30 mph or more, compared with 1,046 on roads of 25 mph or less, even though there are far more miles of 25 mph road.
- Bike lanes help. Only about 15% of crashes happened on a road with a dedicated bike lane.
- Rider behavior matters. When fault was recorded, the e-bike rider was at fault in 82% of crashes.
Based on this, I recommend separating e-bike traffic from cars, by encouraging riders to use slower roads and adding bike lanes where that isn’t possible, and requiring traffic-safety education for e-bike riders.
Explore the crashes on an interactive map (California, 2021–2025).
Presentation
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Related project: mileage estimates
In a separate project, I looked at how accurately people estimate how much they ride and drive. People who received a subsidized e-bike used an app that tracked their mileage and mode of transportation, then filled out a survey estimating how far they had traveled. Each graph shows the gap between a person’s survey estimate and the mileage the app recorded (“Value”): above 0 means they overestimated, below 0 means they underestimated.
After getting an e-bike, people tended to overestimate how much they biked and underestimate how much they drove.
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