title: Statistical analysis of bicyclists' injury severity at unsignalized intersections.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
authors.affiliation: a School of Transportation Engineering, Tongji University , Shanghai , China.
authors.forename: Chen
authors.initials: C
authors.lastname: Wang
authors.forename: Linjun
authors.initials: L
authors.lastname: Lu
authors.forename: Jian
authors.initials: J
authors.lastname: Lu
mesh_terms: D000054:Acceleration; D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D001334:Automobile Driving / Q000331:legislation & jurisprudence; D001642:Bicycling / Q000293:injuries*; D016208:Databases, Factual; D004779:Environment Design / Q000706:statistics & numerical data*; D005260:Female; D006260:Head Protective Devices / Q000706:statistics & numerical data; D006801:Humans; D007629:Kentucky; D008297:Male; D008875:Middle Aged; D016495:Police; D016016:Proportional Hazards Models; D015599:Trauma Severity Indices; D014887:Weather; D055815:Young Adult
keywords: bicyclists; injury severity; partial proportional odds model; unsignalized intersections