Description

To improve traffic safety, communities first need to know where serious crashes are actually happening. High-Injury Networks are designed to identify these locations, but they are usually built using only police-reported crash data. This research asks: Are we missing crashes—and injuries—by relying on police data alone? The research team first demonstrates that data from Emergency Medical Services and those from official databases differ substantially, and neither data set captures the full extent of collisions in a community. Following that analysis, the research team concluded that a new data source may help complete this. Toward that end, the research team scraped data from PulsePoint in San Francisco to identify potential traffic collisions reported to 911 operators. The 911 call data for San Francisco, when compared with official city crash data sources, shows that several traffic incidents reported on 911 calls do not appear in the city’s official database. Statistical analysis of data from both sources vs. those found in only one of the two reveals patterns by location. Locations in police districts with lower population density (and larger geographical areas) had more 911 call-reported incidents that did not appear in the official database. The demographics of census tracts of the incident’s reported location, such as income, race, and education levels, did not appear to be statistically significant. Based on the findings, the research team provides a framework for complementing collision data with alternative sources beyond the police records in future Vision Zero efforts. The research project also resulted in a process that allows the team to continuously add to the scraped 911 call data, enabling this analysis to continue beyond what is presented in this report. When serious injuries are invisible in the data, they are invisible in safety planning. Integrating and using all available data is critical to ensuring that Vision Zero strategies reflect real-world injury risk and deliver meaningful, life-saving outcomes.

Publication Date

4-14-2026

Publication Type

Report

Topic

Planning and Policy, Transportation Engineering, Transportation Technology

Digital Object Identifier

10.31979/mti.2025.2459

MTI Project

2459

Keywords

Transportation safety, Crash data, Vulnerable road users, Demographics, Spatial analysis

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