Establishing the relationship between crashes and unsafe driver behaviors in motorway segments

Surrogate safety analysis is an alternative approach to crash-based analysis for the assessment of traffic safety. Surrogate safety analysis relies in various data types, and it is well admitted that the advancement of technology has enabled the recording of various types of traffic data (e.g., vehicle trajectories) that can be used for safety analysis. However, it is first needed to ensure that these data are correlated with crash data and so, can be used as a proxy of crash data. This study develops crash prediction models for motorway segments using harsh braking and harsh acceleration, and speeding data recorded via a smartphone app. The models indicate that harsh acceleration events are a good predictor of average crash frequency.

• Record URL:
  • https://doi.org/10.1016/j.trpro.2023.11.598
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2352146523008967
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
• Supplemental Notes:
  • © 2023 Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Deliali, Aikaterini
  • Ziakopoulos, Apostolos
  • Dragomanovits, Anastasios
  • Handanos, Ioannis
  • Karadimas, Christos
  • Kostoulas, George
  • Frantzola, Eleni Konstantina
  • Yannis, George
• Conference:
  • Transport Research Arena Conference (TRA Lisbon 2022)
  • Location: Lisbon , Portugal
  • Date: 2022-11-14 to 2022-11-17
• Publication Date: 2023

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 1357-1363
• Serial:
  • Transportation Research Procedia
  • Volume: 72
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2352-1465
  • Serial URL: http://www.sciencedirect.com/science/journal/23521465/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Crash data; Crash risk forecasting; Driving behavior; Mechanical acceleration; Traffic data; Traffic safety
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Safety and Human Factors;

Filing Info

• Accession Number: 01913535
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 1 2024 9:16AM