Use of Real-Time Traffic and Signal Timing Data in Modeling Occupant Injury Severity at Signalized Intersections

This study explored the use of real-time traffic events and signal timing data to determine the factors influencing the injury severity of vehicle occupants at intersections. The analysis was based on 3?years (2017–2019) of crash and high-resolution traffic data. The best fit regression was first identified by comparing the conventional regression model and logistic models with random effect. The logistic model with a heavy-tailed distribution random effect best fitted the data set, and it was used in the variable assessment. The model results revealed that about 13.6% of the unobserved heterogeneity comes from site-specific variations, which underlines the need to use the logistic model with a random effect. Among the real-time traffic events and signal-based variables, approach delay and platoon ratio significantly influenced the injury severity of vehicle occupants at 90% Bayesian credible interval. Additionally, the manner of a collision, occupant seat position, number of vehicles involved in a crash, gender, age, lighting condition, and day of the week significantly affected the vehicle occupant injury. The study findings are anticipated to provide valuable insights to transportation agencies for developing countermeasures to mitigate the crash severity risk proactively.

• Record URL:
  https://doi.org/10.1177/03611981211047836
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/03611981
• Supplemental Notes:
  • Angela E. Kitali https://orcid.org/0000-0002-1962-162X © National Academy of Sciences: Transportation Research Board 2021.
• Authors:
  • Kidando, Emmanuel
  • Kitali, Angela E
  • 0000-0002-1962-162X
  • Kutela, Boniphace
  • 0000-0002-5450-1623
  • Karaer, Alican
  • 0000-0002-6704-0379
  • Ghorbanzadeh, Mahyar
  • 0000-0002-5651-7573
  • Koloushani, Mohammadreza
  • 0000-0002-3896-1662
  • Ozguven, Eren E
• Publication Date: 2022-2

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 825-839
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Volume: 2676
  • Issue Number: 2
  • Publisher: Sage Publications, Incorporated
  • ISSN: 0361-1981
  • EISSN: 2169-4052
  • Serial URL: http://journals.sagepub.com/home/trr

Subject/Index Terms

• TRT Terms: Bayes' theorem; Crash severity; Data analysis; Data models; Distributions (Statistics); Highway safety; Injury severity; Signalized intersections; Traffic signal timing
• Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01763549
• Record Type: Publication
• Report/Paper Numbers: TRBAM-21-04444
• Files: TRIS, TRB, ATRI
• Created Date: Feb 4 2021 10:54AM