Statistical Analysis of Bicyclists’ Injury Severity at Unsignalized Intersections

Abstract

Objectives: This study investigated factors correlated with the severity of injuries sustained by bicyclists in bicycle–motor vehicle crashes at unsignalized intersections to develop site-specific countermeasures and interventions to improve bicycle safety.

Method: Crash data were extracted from accident reports entered into the Kentucky State Police's Kentucky Collision Database in 2002–2012. A partial proportional odds model was developed for data analysis.

Results: According to our modeling results, stop-controlled intersections, one-lane approaches, helmet usage, and lower speed limits were associated with decreased injury severity, whereas uncontrolled intersections, older (age > 55) drivers and bicyclists, child (age < 16) bicyclists, foggy and rainy weather, inadequate use of lights in dark conditions, and wet road surfaces were linked with increased injury severity.

Conclusions: Based on these results, we suggest the development of educational programs focused on the following groups: child bicyclists, older bicyclists, and older drivers. Investigating and modifying street lighting could improve bicycle safety. Implementing road diets/traffic calming methods could create a safer traffic environment. Certain traffic control strategies (e.g., stop control) could be considered for uncontrolled intersections with high bicycle exposure, and helmet campaigns should be launched to increase helmet awareness and use. The study also suggests some interesting future research directions, including examining driver/bicyclist behaviors at uncontrolled intersections and studying the riding behaviors of child bicyclists in Kentucky.

Keywords:

• injury severity
• partial proportional odds model
• bicyclists
• unsignalized intersections

Acknowledgments

The authors wish to thank the four anonymous reviewers whose constructive suggestions helped improve the article.