Balancing Safety and Equity in Traffic Enforcement: An Analysis of Automated Speed Enforcement in Oakland

This report evaluates Oakland’s speed camera pilot through a safety and equity lens, using a thorough academic literature review, descriptive analysis of Oakland Police Department stop data, spatial analysis of speeding-related crashes, regression models, and comparative case studies from San Francisco, Washington, D.C., and Portland, Oregon. Findings show that officer-based traffic enforcement has deeply declined since 2020, leaving a large gap in traffic enforcement that automated cameras appear to be positioned to fill. Spatial analysis shows that speeding-related crashes are highly concentrated along major corridors in East Oakland and Hispanic/Latino communities experience higher exposure to the effects of speeding. Additionally, road width and speeding appear to have a very strong relationship, especially on Hegenberger Road. Our regression analyses indicate that camera placement is strongly associated with crashes, rather than race, income, or age alone—suggesting that Oakland’s implementation is largely data-driven. Our comparative case studies further demonstrate that automated speed enforcement can substantially reduce speeding across different U.S. municipalities.