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Injury Severity of Bus–Pedestrian Crashes in South Korea Considering the Effects of Regional and Company Factors

Author

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  • Ho-Chul Park

    (Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816-2450, USA)

  • Yang-Jun Joo

    (Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Korea)

  • Seung-Young Kho

    (Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Korea)

  • Dong-Kyu Kim

    (Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Korea)

  • Byung-Jung Park

    (Department of Transportation Engineering, Myongji University, Yongin 17058, Korea)

Abstract

Bus–pedestrian crashes typically result in more severe injuries and deaths than any other type of bus crash. Thus, it is important to screen and improve the risk factors that affect bus–pedestrian crashes. However, bus–pedestrian crashes that are affected by a company’s and regional characteristics have a cross-classified hierarchical structure, which is difficult to address properly using a single-level model or even a two-level multi-level model. In this study, we used a cross-classified, multi-level model to consider simultaneously the unobserved heterogeneities at these two distinct levels. Using bus–pedestrian crash data in South Korea from 2011 through to 2015, in this study, we investigated the factors related to the injury severity of the crashes, including crash level, regional and company level factors. The results indicate that the company and regional effects are 16.8% and 5.1%, respectively, which justified the use of a multi-level model. We confirm that type I errors may arise when the effects of upper-level groups are ignored. We also identified the factors that are statistically significant, including three regional-level factors, i.e., the elderly ratio, the ratio of the transportation infrastructure budget, and the number of doctors, and 13 crash-level factors. This study provides useful insights concerning bus–pedestrian crashes, and a safety policy is suggested to enhance bus–pedestrian safety.

Suggested Citation

  • Ho-Chul Park & Yang-Jun Joo & Seung-Young Kho & Dong-Kyu Kim & Byung-Jung Park, 2019. "Injury Severity of Bus–Pedestrian Crashes in South Korea Considering the Effects of Regional and Company Factors," Sustainability, MDPI, vol. 11(11), pages 1-17, June.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:11:p:3169-:d:237480
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    References listed on IDEAS

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    1. Huang, Helai & Song, Bo & Xu, Pengpeng & Zeng, Qiang & Lee, Jaeyoung & Abdel-Aty, Mohamed, 2016. "Macro and micro models for zonal crash prediction with application in hot zones identification," Journal of Transport Geography, Elsevier, vol. 54(C), pages 248-256.
    2. Nadia Solaro & Pier Ferrari, 2007. "Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(1), pages 51-67, June.
    3. Bruno ARPINO & Roberta VARRIALE, 2010. "Assessing The Quality Of Institutions’ Rankings Obtained Through Multilevel Linear Regression Models," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(1(11)_Spr), pages 7-22.
    4. Maas, Cora J. M. & Hox, J.J.Joop J., 2004. "The influence of violations of assumptions on multilevel parameter estimates and their standard errors," Computational Statistics & Data Analysis, Elsevier, vol. 46(3), pages 427-440, June.
    5. Alfonso Montella & Vittorio Marzano & Filomena Mauriello & Roberta Vitillo & Roberto Fasanelli & Mariano Pernetti & Francesco Galante, 2019. "Development of Macro-Level Safety Performance Functions in the City of Naples," Sustainability, MDPI, vol. 11(7), pages 1-21, March.
    6. Abdel-Aty, Mohamed & Lee, Jaeyoung & Siddiqui, Chowdhury & Choi, Keechoo, 2013. "Geographical unit based analysis in the context of transportation safety planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 62-75.
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    Cited by:

    1. Seunghoon Park & Dongwon Ko, 2020. "Investigating the Factors Influencing Pedestrian–Vehicle Crashes by Age Group in Seoul, South Korea: A Hierarchical Model," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    2. Lei Yang & Mahdi Aghaabbasi & Mujahid Ali & Amin Jan & Belgacem Bouallegue & Muhammad Faisal Javed & Nermin M. Salem, 2022. "Comparative Analysis of the Optimized KNN, SVM, and Ensemble DT Models Using Bayesian Optimization for Predicting Pedestrian Fatalities: An Advance towards Realizing the Sustainable Safety of Pedestri," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    3. Wenlong Tao & Mahdi Aghaabbasi & Mujahid Ali & Abdulrazak H. Almaliki & Rosilawati Zainol & Abdulrhman A. Almaliki & Enas E. Hussein, 2022. "An Advanced Machine Learning Approach to Predicting Pedestrian Fatality Caused by Road Crashes: A Step toward Sustainable Pedestrian Safety," Sustainability, MDPI, vol. 14(4), pages 1-18, February.

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