Improving Bicycle Crash Prediction for Urban Road Segments

Sirisha Kothuri, Portland State University



The 2010 Highway Safety Manual (HSM) provides methods for predicting the number of motor vehicle crashes on various roadway facilities (AASHTO, 2010). However, it includes only a simplistic method for predicting the number of bicycle-related crashes. The research team investigated the bicycle-specific crash data in eight potential study areas around the U.S.: Arlington, VA (city/county); Bellingham, WA (city); Boulder, CO (city); Denver, CO (city/county); Minneapolis and St. Paul, MN (cities); Philadelphia, PA (city/county); Portland, OR (city); and San Diego, CA (county). The available online data from each were compared. The study city for future analysis (Boulder) was selected based on the availability of not just crash data but also the availability of continuous and short-duration bicycle and pedestrian traffic count data. In this analysis, a negative binomial model with log link was used to predict annual, non-fatal, motorist-bicyclist crashes on road segments per mile. This report adopts methods from the HSM used for motor vehicle safety performance functions (SPFs) in order to develop bicyclespecific SPFs for roadway segments in Boulder (9). The analysis shows that motor vehicle volume is a leading factor associated with more crashes between motor vehicles and bicyclists. Bicyclist exposure, population density, and percent retail land use are also predictive. While both vehicle volume and bicycle volume data are used in the model in order to account for the “safety in numbers” effect, the model did not demonstrate this effect that is seen so commonly in other research, including the bicycle SPF developed previously for intersections in Boulder (11). This effort at developing a bicycle-specific SPF for segments in the U.S. that utilize bicycle volumes is an important first step towards further understanding bicyclist safety and may inform future versions of the HSM. To that end, the report includes a table of motorist-cyclist crashes predicted future efforts to by the model for various values. The authors hope this table may serve as a potential format template and starting point for generalize the results of models for possible use in HSM updates


The objective of this project is to estimate bicycle volumes at signalized intersections and develop safety performance functions for bicyclists in order to improve bicycle crash prediction. While the Highway Safety Manual currently provides a tool to estimate bicycle crashes, more research is needed to improve the tool. The outcomes from this research are broad in several ways. First, this research will provide a methodology to develop factors to estimate bicycle volumes from continuous counters to be applied to short-term counts. This methodology will be beneficial to practitioners across the US, as currently there is interest in developing performance measures such as annual average daily bicyclists and bicycle miles traveled. Second, this research will provide methods to improve bicycle crash prediction by developing safety performance functions, which can inform and supplement the methods provided in HSM by advancing the state of research. By suggesting a practical way to improve the bicycle crash prediction in the HSM, this work will inform future research on the topic and may lead to a transformation of practice regarding bicycle safety. Finally, the results of this research will be disseminated via the appropriate TRB standing committees and have the potential to advance the state of research with respect to bicycle crash prediction. More broadly, this research will inform planning and policymaking efforts as well as increase our overall understanding of bicycling safety in a world where this mode of travel continues to flourish. 

Project Details

Project Type:
Project Status:
End Date:
December 31,2017
UTC Grant Cycle:
Natl Round 1
UTC Funding:

Other Products

  • Biyclist Safety Performance Functions for Road Segments in a U. S. City (PRESENTATION)
  • Motorist-Cyclist Crash Data Needs in U.S. Communities (PRESENTATION)
  • Motorist-Cyclist Crash Data Needs in U.S. Communities (PRESENTATION)
  • Motorist-Cyclist Crash Data Needs in U.S. Communities (PRESENTATION)
  • Proceedings of the 96th Annual Meeting of the Transportation Research Board (PUBLICATION)