Data-Driven Intersection Safety Evaluation Methodology and Analysis

With the development of information and sensing technologies, a wide variety of intersection traffic data is available. The purpose of this paper is to make full use of video and commercial vehicle trajectory data to deeply explore the intersection safety status. In this paper, based on different sample sizes, different sampling frequencies, and different accuracies of data, the safety analysis of intersections is carried out from micro and macro aspects based on post-encroachment time (PET) and vehicle deceleration behavior, respectively. On the one hand, the authors use the full-sample and high-precision trajectory data extracted from video to analyze the safety of each region of intersection based on PET. On the other hand, using the trajectory data with low penetration rate and low sampling frequency extracted from the positioning data of the online car-hailing, a distribution fit, and non-parametric test are conducted for the vehicle deceleration behavior, and then the overall safety state of the intersection is evaluated. The results can provide ideas for the identification of intersection risk points and the application of different kinds of data on intersection safety evaluation.

• Record URL:
  • https://doi.org/10.1061/9780784485040.027
• Record URL:
  • https://ascelibrary.org/doi/10.1061/9780784485040.027
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784485040
• Supplemental Notes:
  • © 2023 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Wu, Pingping
  • Lu, Guangquan
  • Liu, Miaomiao
• Conference:
  • 23rd COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2023-7-14 to 2023-7-17
• Publication Date: 2023

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 274-283
• Monograph Title: CICTP 2023: Emerging Data-Driven Sustainable Technological Innovation in Transportation

Subject/Index Terms

• TRT Terms: Data fusion; Deceleration; Highway safety; Intersections; Traffic data; Vehicle trajectories
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01909663
• Record Type: Publication
• ISBN: 9780784485040
• Files: TRIS, ASCE
• Created Date: Feb 23 2024 4:23PM