Citation

Habibzadeh M, Ayar P, Mirabimoghaddam MH, Ameri M, Sadat Haghighi SM. J. Adv. Transp. 2023; 2023: e8089395.

Copyright

(Copyright © 2023, Institute for Transportation, Publisher John Wiley and Sons)

DOI

10.1155/2023/8089395

PMID

unavailable

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.

Language: en