Red light running behavior of bicyclists in urban area: Effects of bicycle type and bicycle group size

Bicyclists are vulnerable to fatality and severe injury in road crashes. Red light running violation of bicyclists is the major contributory factors to the crash involvement of bicyclists worldwide. This study aims to identify the factors that affect the propensity of red light running of bicyclists. Effects of bicycle type and bicycle group size are considered. Video observation surveys were conducted at eight signalized intersections in the urban area of Nanjing City in China. Crossing behaviors of 6,930 bicyclists were recorded. Then, a random-parameter logit model was established to measure the association between the propensity of red light running of bicyclist and possible factors. Results indicated that the propensity of red light running of e-bike riders was significantly higher than that of conventional bicyclists. Additionally, factors including bicyclists’ demographics, bicycle group size, traffic flow condition, road geometry and traffic control attributes also affected the propensity of red light running of bicyclists. Propensity of red light running of bicyclist decreased with the increase in the bicycle group size. Propensity increased with the increase in bicycle volume but declined when the opposing traffic volume increased. Presence of signal countdown display was correlated to the increase in the propensity of red light running. Furthermore, interaction effects between bike type and factors including bicyclists’ age, bicycle group size and bicycle volume on the propensity of red light running were significant. These findings can enhance the understanding of red light running behaviors of bicyclists. Also, useful recommendations that can deter against red light running behaviors and enhance overall road safety were provided.

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01751052
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 29 2020 3:05PM