Abstract
Crash rates are an essential tool enabling researchers and practitioners to assess whether a location is truly more dangerous, or simply serves a higher volume of vehicles. Unfortunately, this simple crash rate is far more difficult to calculate for bicycles due to data challenges and the fact that they are uniquely exposed to both bicycle and automobile volumes on shared roadways. Bicycle count data, though increasingly more available, still represents a fraction of the available count data for automobiles. Further compounding on this, bicycle demand estimation methods often require more data than automobiles to account for the high variability that bicycle demand is subject to. This paper uses a combination of mixed methods to overcome these challenges and to perform an investigation of crash rates and exposure to different traffic volumes.
Published Version
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