Authors
1
Associate Professor, Department of Engineering, Tarbiat Modares University, Tehran, Iran
2
Member of the Academic Board, Transportation Research Institute, Ministry of Roads and Transportation, Tehran, Iran
3
Ph. D. Candidate, Department of Engineering, Tarbiat Modares University, Tehran, Iran
Abstract
The appropriate allocation of development budget for the safety upgrading of roads is one of the most specific safety management criteria in the roads. Determining the high risk areas and their prioritization for their accident probability is the fundamental step for planning of the roads safety.The determination of the risk of an area, is usually implemented by the investigating the frequency of accidents, rate of accidents, and the intensity of accidents. In this paper making use of Bayesian Theory, a method for determination of the risk in various points in a road and their prioritization is developed. In this method, on the basis of present information on accidents in one section, (which may be according to the engineering judgment or the statistics of accidents in the past years), the accident risk of the section is estimated and then by observation the real accidents occurred up to the end of the year, the risk rate of that section is estimated. Then these areas (which are similar to each other from traffic and geometrical points of view) are prioritized on the basis of their accident probability.One of the major factors in prediction of accidents in an accident prone section is the number of occurred accidents there. The greater the number of accidents compared to the traffic volume, the higher the number of risky factors. The second factor responsible for the accident probability of a section in the road is the intensity of accidents. The ratio of accidents which are ended to death toll, to the total number of accidents on that section is the intensity rate of accidents. Therefore in this research the accident prone areas are prioritized according to both parameters for their probability of accidents.The behavior of a section in the road for its accident proneness should be specified according to the distribution function of accidents there, to the traffic volume on that section. The higher the accuracy of fitting of a distribution functions on the accidents statistics, the more precise will be the prediction of accidents in the future. In this paper a model has been developed on the basis of Bayesian theory for determination of the risk rate of an area. The accuracy of the developed method comparing to other models is higher, in case of availability if some pert data in the study. By using this method it would be possible to determine the safety criteria for all the similar points through sampling of some points and studying their characteristics. Not to mention that the developed method, although is one of the statistical inference methods, but is sensitive towards its preliminary assumptions which are the former distribution function and the risk function. Due to sampling of similar areas, the Bayesian Method is more accurate for determination of the risk factor compared to classic methods.
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