Jamal Al-Matawah1, a and Khair Jadaanb

a Department of Civil Engineering, College of Technological Studies in Kuwait
Department of Civil Engineering, University of Jordan


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ABSTRACT


The dramatic increase in vehicle travel in developing countries calls for the effective introduction of features that reduce traffic accidents. An important piece of information for such an introduction lies in the prediction of accidents and their fatalities, which is addressed in this paper. Smeed’s model was originally developed for the prediction of traffic fatalities in both developed and developing countries. More reliable prediction models are developed for a number of Arab countries, producing a much less absolute percentage error than those of Smeed’s model. Regression analysis was applied to time-series data in the studied countries, producing an absolute percentage error as low as 7.67 for Saudi Arabia and 12.17 for Kuwait. An accident prediction model that relates accident frequency in Kuwait to various contributory factors is developed using the Generalized Linear Modelling (GLM) technique. The final model shows that age, nationality, aggressive driver behaviour, dangerous offences, perception of effectiveness of enforcement, marital status, speed, and experience are the main contributory factors that lead to accident involvement.


Keywords: road safety; prediction models; developing countries.


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REFERENCES


  1. [1] Murray C. and Lopez A. 1996. In: C. Murray and A. Lopez, Editors, “The Global Burden of Disease”. Harvard Press, Cambridge, MA.

  2. [2] Haight, F. A. 1980. Traffic safely in developing countries. Journal of Safety Research, 12: 50-58.

  3. [3] Jacobs, G., Aeron-Thomas, A. and Astrop, A., 2000. “Estimating Global Road Fatalities”. TRL Report 445. Transporting Research Laboratory, London, England.

  4. [4] Bener A, Ofsu J. B. 1991. Road traffic fatalities in Saudi Arabia. Journal of India Association Traffic and safety Science, 15: 35-38.

  5. [5] Elvik, R. 1995. Analysis of official economic valuations of traffic accident fatalities in 20 motorized countries. Accident analysis and Prevention, 27: 237-47.

  6. [6] Bishai, D. 2005. Traffic fatalities and economic growth. Accident analysis and Prevention, 37: 169-78.

  7. [7] Bishai D., Quresh A., James P., and Ghaffar, A. 2006. National road casualties and economic development. Health Economics, 15: 65-81.

  8. [8] Kopits, E. and Cropper, M. 2005. Traffic fatalities and economic growth. Accident analysis and Prevention, 37: 169-78.

  9. [9] Smeed, R. J. 1949. Some statistical aspects of road safety research. Journal of the Royal Statistical Society: Series A, 12, 1: 1-23.

  10. [10] Jadaan, K. S. 1982. A study of accident rates in Kuwait. Journal of the University of Kuwait (science) 9: 41-50.

  11. [11] Jadaan, K. S., Alenezi, F. and AlZahrani, A. 1992. Road fatalities in Saudi Arabia; Trends and prediction, Proceeding of the REAAA workshop, 3: 19-24.

  12. [12] Jadaan, K. S., Khalil R. and Bener A. 1991. A mathematical model using convex combination for the prediction of the road traffic deaths. Journal of Computing and information, 2: 139-157.

  13. [13] McCullagh, P. and Nelder, J. A. 1983. “Generalized Linear Model”. London: Chapman and Hall.

  14. [14] Chatterjee, S., Hadi, A. S., Price, B. 2000. “Regression analysis by example”. New York, Chichester: Wiley and Sons.


ARTICLE INFORMATION




Accepted: 2010-09-07
Available Online: 2010-10-01


Cite this article:

Al-Matawah, J., Jadaan, K. 2010. Application of prediction techniques to road safety in developing countries. International Journal of Applied Science and Engineering, 8, 11–17. https://doi.org/10.6703/IJASE.2010.8(1).11