Operational Research in Engineering Sciences

Journal DOI: https://doi.org/10.31181/oresta190101s

(A Journal of Management and Engineering) ISSN 2620-1607 | ISSN 2620-1747 |

Models for ranking railway crossings for safety improvement

Sandra Kasalica,
Academy of Technical and Art Applied Studies Belgrade, department High Railway School, Belgrade, Serbia
Marko Obradović,
Faculty of Mathematics, University of Belgrade, Belgrade, Serbia
Aleksandar Blagojević,
Academy of Technical and Art Applied Studies Belgrade, department High Railway School, Belgrade, Serbia
Dušan Jeremić,
Academy of Technical and Art Applied Studies Belgrade, department High Railway School, Belgrade, Serbia
Milivoje Vuković,
Infrastructure of Serbian Railways, Belgrade, Serbia

Abstract

Analysis of high-risk locations, accident frequency and severity for railway crossing is necessary in order to improve the safety and consequently diminish the number of accidents and their severity. In order to extract the necessary parameters that quantify the risk associated with railway crossings in Serbia, we have carefully analyzed available statistical models commonly used in this kind of studies. A zero-inflated Poisson model and a multinomial logistic model were used for the assessment of accident frequency and accident severity respectively. In order to quantitatively evaluate the risk, a well known measure – total risk was modified and a new measure for risk – empirical risk was introduced. The road sign warning device (p=2.76∙10^(-9)) , exposure to traffic (p=4.3∙10^(-7)), and maximum train speed at a given crossing were (p=1.36∙10^(-5)) significantly associated with probability of accident frequency and significantly influenced the expected total number of fatalities or injuries caused by traffic accidents.

Keywords
railway crossings, high-risk locations, accidents, regression models.

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SCImago Journal & Country Rank

CiteScore for Management Science and Operations Research

8.1
2021CiteScore
 
 
89th percentile
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CiteScore for Engineering (miscellaneous)

8.1
2021CiteScore
 
 
93rd percentile
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