Research on Crossing Behavior of Nonmotorized Vehicles at Signalized Intersections Based on Survival Analysis

To study the irregularities of non-motorized vehicles at signalized intersections, seven signalized intersections in Xi'an were selected to acquire video data by aerial photography. The data were analyzed using SPSS data analysis software, and the overall survival function was drawn using the Kaplan-Meier analysis method. This study develops a Cox hazard-based model and a binomial logit model to analyze the factors that influence non-motorized vehicle irregularities at signalized intersections comparatively. The results show that about 20 percent of cyclists do not wait, and about 20 percent abide by traffic rules strictly. Six factors, including non-motor vehicle type and motor vehicle traffic volume in conflict direction, have significant effects on the waiting time of non-motor vehicles crossing at signalized intersections. Compared with the binomial logit model, the Cox hazard-based model has a better fitting effect.

• Record URL:
  • https://doi.org/10.1061/9780784481523.183
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
• Supplemental Notes:
  • © 2018 American Society of Civil Engineers 2018
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Ma, Shuhong
  • Liu, Chuanqi
• Conference:
  • 18th COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2018-7-5 to 2018-7-8
• Publication Date: 2018-7

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 1847-1855
• Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility

Subject/Index Terms

• TRT Terms: Behavior; Cyclists; Data analysis; Signalized intersections; Survival; Traffic safety
• Geographic Terms: Xi'an (China)
• Subject Areas: Highways; Pedestrians and Bicyclists;

Filing Info

• Accession Number: 01870115
• Record Type: Publication
• ISBN: 9780784481523
• Files: TRIS, ASCE
• Created Date: Jan 19 2023 11:23AM