Investigation of Road Accident Severity per Vehicle Type

The aim of the present study is the investigation of road accident severity per vehicle type. For that reason, a dataset consisting of 59,316 recorded accidents in Greece was analyzed and mathematical models were developed by applying lognormal regression. Three expressions of accident severity were examined: i) the number of fatalities divided by the total number of involved vehicles, ii) the number of severe injuries divided by the total number of involved vehicles and iii) the number of slight injuries divided by the total number of involved vehicles. Furthermore, separate accident severity models were developed for each type of vehicle. The effect of various parameters, such as crash type and weather conditions on accident severity was identified for each type of vehicle (car, moped, motorcycle, bus and truck). Cars involve both private vehicles as well as vehicles used for commercial purposes (like taxis). In general, good weather conditions and night accidents increase severity. Moreover, crash types are consistently affecting accident severity.

• Record URL:
  https://doi.org/10.1016/j.trpro.2017.05.401
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S2352146517307081
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
• Supplemental Notes:
  • © 2017 Yannis George et al. Published by Elsevier B.V.
• Authors:
  • George, Yannis
  • Athanasios, Theofilatos
  • George, Pispiringos
• Conference:
  • World Conference on Transport Research - WCTR 2016
  • Location: Shanghai , China
  • Date: 2016-7-10 to 2016-7-15
• Publication Date: 2017

Language

• English

Media Info

• Media Type: Digital/other
• Features: References; Tables;
• Pagination: pp 2076-2083
• Serial:
  • Transportation Research Procedia
  • Volume: 25
  • 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 injuries; Crash severity; Crash types; Multiple vehicle crashes; Nighttime crashes; Traffic crashes; Weather conditions
• Geographic Terms: Greece
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01642404
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 27 2017 2:15PM