Prioritization of Suburban Accident Factors Based on Analytical Network Process

The safety management of transportation system leads to decrease in a number of traffic accidents. Identification of the primary reasons in accident incidence is the initial step in controlling the crashes. The source of accidents is divided into 3 groups; namely, human, environment and traffic. Due to the complex nature of traffic accidents, Multi-Criteria Decision-Making (MCDM) methods can be considered as an efficient approach. The main objective of the paper was to use analytical network process (ANP) to evaluate the interaction of human, traffic and road related parameters in occurrence of accidents. ANP is the extended form of analytical hierarchy process (AHP). AHP simulates a decision problem into a hierarchy consists of a goal, decision criteria, and alternatives, while the ANP structures that as a network. Next step is to use pair wise comparisons to calculate the weights of the components of the structure, and to rank the alternatives in the decision. The power of the ANP lies in its use of ratio scales to capture all kinds of interactions and make accurate predictions. In this paper, using ANP structure, instead of pair wise comparison made by experts’ opinion in calculation of the weight of components; statistic analysis as well as frequency of effective parameters in accident occurrence, were utilized where statistics was available. This was resulted in more accurate outcomes.  Sub-urban accidents data in the length of 945 km of Hamedan province in three-year period was considered as a case study. As a result, although most of the researchers are of the idea that the human plays a crucial role in crash occurrence, road factors had higher priority. Factors such as curvature and grade were more effective than human characteristics. Furthermore, it was concluded that, Condition curvature (0-100) degree per kilometer and grade (0-3%) had higher risk of accidents.