IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i22p4354-d977869.html
   My bibliography  Save this article

Analysis of the Accident Propensity of Chinese Bus Drivers: The Influence of Poor Driving Records and Demographic Factors

Author

Listed:
  • Lili Zheng

    (Transportation College, Jilin University, No. 5988 Renmin Street, Changchun 130022, China)

  • Xinyu He

    (Transportation College, Jilin University, No. 5988 Renmin Street, Changchun 130022, China)

  • Tongqiang Ding

    (Transportation College, Jilin University, No. 5988 Renmin Street, Changchun 130022, China)

  • Yanlin Li

    (Transportation College, Jilin University, No. 5988 Renmin Street, Changchun 130022, China)

  • Zhengfeng Xiao

    (Transportation College, Jilin University, No. 5988 Renmin Street, Changchun 130022, China)

Abstract

Previous studies have shown that bus drivers are a major contributing factor to bus accidents. The aim of this study is to explore the factors that contribute to the presence of accident propensity among bus drivers, as well as the relative importance of each influencing factor and the mechanism of influence. To this end, a C5.0 decision tree model was developed to determine the relative importance as well as rank the importance of the impact of poor driving records and demographic factors on accident propensity, and a binary logistic regression model was developed to analyze the relationship between accident propensity and the different values of each essential influencing factor. Based on our results, we found that: (1) the number of violations had the most significant effect on bus drivers’ accident propensity, followed by age, driving age, and number of alarms; (2) violations and alarms are positively related to bus driver accident propensity; age and driving age are inversely related to bus driver accident propensity; and (3) men have a higher accident risk probability than women. This study’s findings will help bus companies and traffic management authorities to implement more targeted improvements to their bus driver management programs.

Suggested Citation

  • Lili Zheng & Xinyu He & Tongqiang Ding & Yanlin Li & Zhengfeng Xiao, 2022. "Analysis of the Accident Propensity of Chinese Bus Drivers: The Influence of Poor Driving Records and Demographic Factors," Mathematics, MDPI, vol. 10(22), pages 1-20, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4354-:d:977869
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/22/4354/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/22/4354/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aziemah Azhar & Noratiqah Mohd Ariff & Mohd Aftar Abu Bakar & Azzuhana Roslan, 2022. "Classification of Driver Injury Severity for Accidents Involving Heavy Vehicles with Decision Tree and Random Forest," Sustainability, MDPI, vol. 14(7), pages 1-19, March.
    2. Tseng, Chien-Ming, 2012. "Social-demographics, driving experience and yearly driving distance in relation to a tour bus driver’s at-fault accident risk," Tourism Management, Elsevier, vol. 33(4), pages 910-915.
    3. Marina Segura & Jorge Mello & Adolfo Hernández, 2022. "Machine Learning Prediction of University Student Dropout: Does Preference Play a Key Role?," Mathematics, MDPI, vol. 10(18), pages 1-20, September.
    4. Nerea Gómez-Fernández & Mauro Mediavilla, 2022. "Factors Influencing Teachers’ Use of ICT in Class: Evidence from a Multilevel Logistic Model," Mathematics, MDPI, vol. 10(5), pages 1-29, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ratanavaraha, Vatanavongs & Jomnonkwao, Sajjakaj, 2014. "Model of users׳ expectations of drivers of sightseeing buses: confirmatory factor analysis," Transport Policy, Elsevier, vol. 36(C), pages 253-262.
    2. Liya Yue & Pei Hu & Shu-Chuan Chu & Jeng-Shyang Pan, 2023. "Multi-Objective Gray Wolf Optimizer with Cost-Sensitive Feature Selection for Predicting Students’ Academic Performance in College English," Mathematics, MDPI, vol. 11(15), pages 1-16, August.
    3. Almudena Sanjurjo-de-No & Ana María Pérez-Zuriaga & Alfredo García, 2023. "Factors Influencing the Pedestrian Injury Severity of Micromobility Crashes," Sustainability, MDPI, vol. 15(19), pages 1-17, September.
    4. Yasmin, Shamsunnahar & Anowar, Sabreena & Tay, Richard, 2013. "Factors Contributing to School Bus Crashes," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 52(3).
    5. Maria Rodionova & Angi Skhvediani & Tatiana Kudryavtseva, 2022. "Prediction of Crash Severity as a Way of Road Safety Improvement: The Case of Saint Petersburg, Russia," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
    6. Carmen Lacave & Ana Isabel Molina, 2023. "Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education," Mathematics, MDPI, vol. 11(6), pages 1-4, March.
    7. Amini, Mostafa & Bagheri, Ali & Delen, Dursun, 2022. "Discovering injury severity risk factors in automobile crashes: A hybrid explainable AI framework for decision support," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    8. Douglas C. Frechtling & Tadayuki Hara, 2016. "State of the world’s tourism statistics and what to do about it," Tourism Economics, , vol. 22(5), pages 995-1013, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4354-:d:977869. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.