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Classification Trees in the Assessment of the Road–Railway Accidents Mortality

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Listed:
  • Edward Kozłowski

    (Faculty of Management, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland)

  • Anna Borucka

    (Faculty of Security, Logistics and Management, Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland)

  • Andrzej Świderski

    (Motor Transport Institute, ul. Jagiellońska 80, 03-301 Warsaw, Poland)

  • Przemysław Skoczyński

    (Motor Transport Institute, ul. Jagiellońska 80, 03-301 Warsaw, Poland)

Abstract

A special element of road safety research is accidents at the interface of the road and rail system. Due to their low share in the total number of incidents, they are not a popular subject of analyses but rather an element of collective studies, whereas the specificity of the road–rail accidents requires a separate characteristic, allowing, on the one hand, to categorize these types of incidents, and on the other, to specify the factors that affect them, along with an assessment of the strength of this impact. It is important to include in such analyses all potential predictors, both qualitative and quantitative. Moreover, the literature considers most often a number of accidents while, according to the authors, it does not fully reflect the scale of the danger. A better evaluation would be the victim’s degree of injury. Therefore, the purpose of this article is to assess the likelihood of occurrence of various effects of road–rail accidents in the aspect of selected factors. Due to the ordinal form of the dependent variable, the classification trees method was used. The results obtained not only allow the characterization and assessment of the danger but also constitute guidelines for taking preventive actions.

Suggested Citation

  • Edward Kozłowski & Anna Borucka & Andrzej Świderski & Przemysław Skoczyński, 2021. "Classification Trees in the Assessment of the Road–Railway Accidents Mortality," Energies, MDPI, vol. 14(12), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3462-:d:573261
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    References listed on IDEAS

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    1. G. V. Kass, 1980. "An Exploratory Technique for Investigating Large Quantities of Categorical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(2), pages 119-127, June.
    2. Aleksandar Blagojević & Sandra Kasalica & Željko Stević & Goran Tričković & Vesna Pavelkić, 2021. "Evaluation of Safety Degree at Railway Crossings in Order to Achieve Sustainable Traffic Management: A Novel Integrated Fuzzy MCDM Model," Sustainability, MDPI, vol. 13(2), pages 1-20, January.
    3. Rungskunroch, Panrawee & Jack, Anson & Kaewunruen, Sakdirat, 2021. "Benchmarking on railway safety performance using Bayesian inference, decision tree and petri-net techniques based on long-term accidental data sets," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
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