Modeling of accidents in highway-railway grade crossings

Document Type : Research Paper

Authors

1 PhD. Student, Department of Civil Engineering, Iran University of Science and Technology, Tehran, Iran, ,

2 Associate Professor, Department of Railway Engineering, Iran University of Science and Technology, Tehran, Iran

3 Assistant Professor, Department of Civil Engineering, Iran University of Science and Technology, Tehran, ,Iran

4 Iran University of Science and Technology, Tehran, ,Iran

Abstract

Improving the safety of rail transport requires collecting, categorizing and analyzing accident statistics in order to assess and determine the factors affecting rail crashes. HRGCs (highway railway grade crossings) are high-risk areas for all rail lines in the world. Therefore, it is very important to study the factors affecting the formation and severity of railway traffic accidents. The use of statistical models, including the logit model, based on traffic, geometric and accident history, is one of the methods for identifying incident points that, despite the creation of such models for other points such as bridges and road junctions, the prediction of accidents in Iran HRGCs has not been addressed properly. Therefore, in this paper, for the first time, by determining the severity of accidents as a response variable using the Logit model and using data related to the road accidents of Iran Railway Network between 2009 and 2013, the factors affecting the severity of the road accidents can be achieved to reduce the severity of rail accidents and the resulting destructive effects by eliminating these factors. Finally, by using these data the result was that allowed intersections that are not blocked, passenger trains, motorcycles, very high road traffic conditions and high speed trains were known as factors of increasing the severity of accidents and on the other side, the proximity to railway stations, freight trains and agricultural machinery were known as factors of decreasing the severity of accidents.

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References

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History

  • Receive Date: 21 May 2018
  • Revise Date: 10 October 2018
  • Accept Date: 10 October 2018

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