Analysis of the Severity of Accidents on Rural Roads Using Statistical and Artificial Neural Network Methods

Author:

Habibzadeh Mohammad1ORCID,Ayar Pooyan1ORCID,Mirabimoghaddam Mohammad Hassan2,Ameri Mahmoud1,Sadat Haghighi Seyede Mojde1

Affiliation:

1. School of Civil Engineering, Iran University of Science & Technology (IUST), Tehran, Iran

2. Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran

Abstract

This study assesses the relationship that existed between various variables and their subvariables on rural roads in Qom, Iran, using statistical analysis and calculates the relationship between the considered factors and accident severity. A logit model was applied to determine the factors affecting the severity of accidents. In addition, two artificial neural network (ANN) models were developed using two kinds of learning methods to train neurons to select the best result. The results of modeling and analysis of accidents using various techniques revealed that each technique, depending on its purpose, examined the severity of accidents from a different point of view and represented various outcomes. Finally, the performance of the proposed models was validated utilizing other mathematical models. As a result, putting the output results together, the best measures can be suggested to increase the safety of people on rural roads. The outcomes of this study may aid these service providers in strategic planning and policy framework.

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

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