doi: 10.7763/IJET.2012.V4.334
A Study of Structure of Road Accidents Status Prediction Model for Highways
- 1 Department of Civil Engineering, Islamic Azad University, Karaj Branch, Tehran, Iran
- 2 Tehran Industrial Cities, Iran Ministry of Industry, Mine and Trade, Tehran, Iran
- 3 Atisaz Construction Company, Tehran, Iran
- 4 Obermeyer Middle East GmbH, Abu Dhabi, United Arab Emirates
Abstract
With regard to the importance of road accidents and the resulting costs, which include human, economic and social losses, the study and modeling of road accidents will be inevitable in identifying the causal factors of accidents. This article analyzes the construction of a model for the severity of fatal road accidents taking into account of the characteristics of the driver, motor vehicle, road and the environmental conditions of the roads of the country. In order to construct the accidents severity model, the Logit function of fatality likelihood is used. The function’s output varies between zero and one. As the output becomes closer to one the likelihood of fatality will be more, and as it approaches the zero the likelihood of fatality will come down. In such models, such factors as elderly drivers, the existence of motorcycles and bicycles, inattention to the front, exceeding the authorized speed, unauthorized deviation to left due to overtaking, passing unauthorized place, illiteracy of drivers, etc. will increase the severity of accidents, and such factors as clear weather, standard road width, etc. will decrease fatal accidents. The factors are discussed in detail in this article.
Keywords
- Road accident
- highways
- logit model
- accident indexes
How to Cite
Hassan Zoghi, Morteza Tolouei, Kianoush Siamardi, and Mohammad Ramezani Afjadi, "A Study of Structure of Road Accidents Status Prediction Model for Highways," International Journal of Engineering and Technology, vol. 4, no. 2, pp. 135-138, 2012. https://doi.org/ 10.7763/IJET.2012.V4.334
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).