Survival Analysis on Pedestrian's Maximum Waiting Time at Signalized Intersections

In most Chinese cities, the issue of disorder, high risks and low efficiency at signalized intersections is mainly attributed to illegal pedestrian crossing. Pedestrians waiting time before crossing plays a key role in this decision making process. Overlong waiting time will make pedestrians lose patience and result in illegal crossing. In this paper, pedestrians crossing behavior data collected by video camera in 5 directions from branch roads at 3 typical signalized intersections crossed by arterial-road and branch-road were analyzed. First, a survival model of pedestrians waiting time is built with waiting time of legal and illegal crossing pedestrians. And then a COX regression model is established presenting the probability of pedestrians illegal crossing influenced by both pedestrians characteristic and traffic design factors. The result of survival analysis indicates that though 50th percentile pedestrians illegal crossing time in 5 directions ranges from 22 to 49 seconds, 85th percentile pedestrians illegal crossing time shows high conformity of 90s for maximum bearable waiting time, while the value is only 50 seconds at central refuge islands. The analysis of COX model shows that pedestrians maximum waiting time has close relation with conflicting vehicle flow, the time of pedestrian red phase and pedestrians age. Reasonable intersection design and signal control can help to reduce the risk of illegal crossing. This paper concludes the max red phase for pedestrians is suggested not exceed 90 seconds. And at central refuge island, the value should not be over 50s.


  • English

Media Info

  • Media Type: DVD
  • Features: Figures; References; Tables;
  • Pagination: 18p
  • Monograph Title: TRB 89th Annual Meeting Compendium of Papers DVD

Subject/Index Terms

Filing Info

  • Accession Number: 01151109
  • Record Type: Publication
  • Report/Paper Numbers: 10-1428
  • Files: BTRIS, TRIS, TRB
  • Created Date: Feb 23 2010 8:06AM