Study and prioritization of factors affecting the severity of accidents in Gilanti province from 2013 to 2017
The high rate of fatalities on suburban roads is recognized as one of the biggest safety concerns in developing countries. Objective of this study is a descriptive study of the distribution of the number and severity of traffic accidents, according to time, place, weather conditions, type of collision, type and number of vehicles involved, gender of the parties involved, the cause and also to identify the factors. It affects the number and severity of accidents and prioritizes the extent to which each of them affects each other. For this purpose, the data of registered accidents in Chabaksar checkpoint of Guilan province in the period to were received from the traffic police of Guilan province and after coding the accident data of different effective factors recorded by the traffic police of Guilan province in sections Factors as well as prioritizing the impact of these factors were discussed using Friedman test. The results showed that about of accidents occurred on side roads. Also, the highest rate of accidents has occurred in the spring. Also, the age distribution of drivers responsible for accidents showed that the largest share is related to drivers aged to years. Lack of attention to the front is also the most common cause of accidents.
Prediction , Modeling , Accidents , Suburban , LogitModel , Neural Network
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