Modeling Highway Traffic Safety in Nigeria Using Delphi Technique and Bayesian Network

Highway traffic safety is an issue confronting developing countries and those of industrialized nations. Many people are injured and/or killed all over the world daily on highway traffic related crashes. Nigeria, as a developing country, has been experiencing unusually high traffic related injury and fatality rates. In order to commence combating highway safety problems in Nigeria, the first task is to identify the major contributing factors, however, Nigeria has no reliable and comprehensive database of traffic accidents and casualties. Consequently, the Delphi Technique was utilized in generating the required data such as number of registered automobiles, number of licensed drivers, and annual fatality count for modeling and forecasting accident rates in Nigeria. A Bayesian Network Model was developed and used, with the data obtained from Delphi process, to demonstrate possible traffic safety responses to different scenarios of changes in the Nigerian socio-political culture. Although the Delphi Technique and the Bayesian Network Model only estimate the accident and safety data, those methods can be a realistic option when those data are not available, especially for the developing countries. The conclusions that are drawn from the output of the Bayesian Network and the analysis of the research results support the notion that the major accident contributors have been identified and the top three contributors – Road Condition, driving under the influence (DUI), and Reckless Driving - are policy related. The Nigerian traffic safety outlook would improve significantly if the existing laws and policies can be enforced, even at a very moderate level.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABE90 Transportation in the Developing Countries.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Mbakwe, Anthony C
  • Saka, Anthony A
  • Choi, Keechoo
  • Lee, Young-Jae
• Conference:
  • Transportation Research Board 93rd Annual Meeting
  • Location: Washington DC
  • Date: 2014-1-12 to 2014-1-16
• Date: 2014

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 21p
• Monograph Title: TRB 93rd Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Bayes' theorem; Crash causes; Crash data; Delphi method; Developing countries; Drunk driving; Highway factors in crashes; Networks; Reckless drivers; Traffic safety
• Geographic Terms: Nigeria
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I82: Accidents and Transport Infrastructure; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 01519614
• Record Type: Publication
• Report/Paper Numbers: 14-4572
• Files: TRIS, TRB, ATRI
• Created Date: Mar 26 2014 10:07AM