Being able to assess the risk that a person walking or biking will collide with a car could help transportation planners determine the best places to implement safety improvements.

Existing data from crashes, pedestrian and bicyclist counts, and automobile traffic flows can be combined to identify intersections, corridors, or other urban areas with elevated collision risks for bicyclists or pedestrians. As the availability of count data gradually increases because of automation techniques, it will become easier to identify problem areas. In a recent Roadway Safety Institute (RSI) project, University of Minnesota researchers evaluated whether a phenomenon known as “safety in numbers” was observable in crash data collected for Minneapolis, Minnesota—one of the few cities that currently has a sufficiently rich dataset of pedestrian and bicyclist counts to allow for meaningful safety analysis.

Safety in numbers is the hypothesis that an individual has a better chance of avoiding harm or danger in a group than when alone. In the context of traffic safety, that would mean the safety of bicyclists and pedestrians is positively correlated with more biking and walking activity in a given area, says Andrew Owen, director of the University of Minnesota’s Accessibility Observatory. “For example, we would expect to see the per-pedestrian risk of being injured in a crash with a motor vehicle decrease as the number of other pedestrians increases,” he says.

pedestrians walking

For the RSI study, the researchers began by looking at the safety-in-numbers effect for pedestrians in Minneapolis. They analyzed a sample of 488 intersections and determined the relationships between pedestrian traffic flows and the per-pedestrian crash risk. The results indicated that there was, in fact, safety in numbers—pedestrians were at a lower risk of being hit by a car at intersections with more pedestrian traffic, and individual cars were at a lower risk of hitting pedestrians at intersections with more car traffic.

Next, researchers examined how the safety-in-numbers effect applied to bicyclists in the Twin Cities. Using data from 489 intersections, they modeled the number of crashes against the average daily vehicle traffic and the daily bicyclist traffic and measured the accuracy of the model. Again, they found that safety in numbers played a positive role: intersections with more vehicles and cyclists exhibited lower crash rates.

“While the exact cause for the safety-in-numbers effect is not understood, it is still a justification for improving the walkability and bike-ability of urban environments,” Owen says. “By assessing the per-pedestrian and per-bicyclist crash rates at specific locations, as opposed to using crash counts alone, transportation planners and practitioners can more readily identify target areas where improvements to infrastructure may be warranted.”

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