Journal of Transportation Research

Journal of Transportation Research

Statistical analysis and presentation of accident prediction model leading to injuries and deaths of pedestrians in rural roads of Gilan

Document Type : Original Article

Authors
Neda Kamboozia 1
Mahmoud Ameri 2
Seyed Mohsen Hosseinian 3
1 Associate Professor, Department of Civil Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
2 Professor, Department of Civil Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
3 M.Sc., Grad., Department of Civil Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
Abstract
The high number of fatalities on rural road accidents is recognized as one of the biggest safety concerns in developing countries. Modeling the severity of pedestrian accidents according to the effective parameters provides the possibility of predicting the occurrence or non-occurrence of accidents. In addition, this model can be used to examine the impact of each factor on the severity of pedestrian accidents. Therefore, it is possible to identify the factors affecting pedestrian accidents that lead to a decrease in the frequency and severity of accidents. The purpose of this study is to create statistical models to predict the severity of pedestrian accidents on rural areas of Gilan. Therefore, in this study, by collecting information of pedestrian accidents on rural roads in 12 months of 1393 to 1397 in Gilan and using statistical analyses such as Friedman test, factor analysis and Logit model, the probability of occurrence of each category of accidents is calculated. The results of accident modeling and analysis by different methods showed that each of the analysis methods according to their function, examined the severity of accidents from different perspectives and had different results. Therefore, by combining the obtained output results, the best measures can be proposed to increase the safety of rural roads in Gilan.
Keywords
Safety
Rural Accidents
Severity of Accidents
Pedestrians
Modeling
Subjects
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