Citation

Sando T, Mussa R, Sobanjo J, Spainhour L. J. Saf. Res. 2005; 36(5): 485-487.

Affiliation

Department of Civil Engineering and Environmental Engineering, FAMU-FSU College of Engineering, 2525 Pottsdamer Street, Room 129, Tallahassee, FL 32310, USA.

Copyright

(Copyright © 2005, U.S. National Safety Council, Publisher Elsevier Publishing)

DOI

10.1016/j.jsr.2005.10.006

PMID

16298394

Abstract

Modeling of traffic crashes is a complex undertaking. Previous studies have used a variety of techniques to analyze crashes. The choice of the technique to be used in any specific modeling problem can be challenging.The methods that have been mostly used include regression analysis, artificial neural networks, and pattern recognition methods that include nearest neighbor rule and Bayesian belief network technique. The knowledge of the advantages and disadvantages of each method would help safety analysts on deciding the most appropriate method for each particular analysis. This paper provides an insight on the advantages and disadvantages of each of the aforementioned group of methods.