IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i23p12725-d693610.html
   My bibliography  Save this article

Insights into Factors Affecting Traffic Accident Severity of Novice and Experienced Drivers: A Machine Learning Approach

Author

Listed:
  • Shuaiming Chen

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Haipeng Shao

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Ximing Ji

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

Abstract

Traffic accidents have significant financial and social impacts. Reducing the losses caused by traffic accidents has always been one of the most important issues. This paper presents an effort to investigate the factors affecting the accident severity of drivers with different driving experience. Special focus was placed on the combined effect of driving experience and age. Based on our dataset (traffic accidents that occurred between 2005 and 2021 in Shaanxi, China), CatBoost model was applied to deal with categorical feature, and SHAP (Shapley Additive exPlanations) model was used to interpret the output. Results show that accident cause, age, visibility, light condition, season, road alignment, and terrain are the key factors affecting accident severity for both novice and experienced drivers. Age has the opposite impact on fatal accident for novice and experienced drivers. Novice drivers younger than 30 or older than 55 are prone to suffer fatal accident, but for experienced drivers, the risk of fatal accident decreases when they are young and increases when they are old. These findings fill the research gap of the combined effect of driving experience and age on accident severity. Meanwhile, it can provide useful insights for practitioners to improve traffic safety for novice and experienced drivers.

Suggested Citation

  • Shuaiming Chen & Haipeng Shao & Ximing Ji, 2021. "Insights into Factors Affecting Traffic Accident Severity of Novice and Experienced Drivers: A Machine Learning Approach," IJERPH, MDPI, vol. 18(23), pages 1-20, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12725-:d:693610
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/23/12725/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/23/12725/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guofa Li & Weijian Lai & Xingda Qu, 2020. "Association between Crash Attributes and Drivers’ Crash Involvement: A Study Based on Police-Reported Crash Data," IJERPH, MDPI, vol. 17(23), pages 1-16, December.
    2. Chen Wang & Lin Liu & Chengcheng Xu & Weitao Lv, 2019. "Predicting Future Driving Risk of Crash-Involved Drivers Based on a Systematic Machine Learning Framework," IJERPH, MDPI, vol. 16(3), pages 1-18, January.
    3. Ivers, R. & Senserrick, T. & Boufous, S. & Stevenson, M. & Chen, H.-Y. & Woodward, M. & Norton, R., 2009. "Novice drivers' risky driving behavior, risk perception, and crash risk: Findings from the DRIVE study," American Journal of Public Health, American Public Health Association, vol. 99(9), pages 1638-1644.
    4. Qiang Zeng & Wei Hao & Jaeyoung Lee & Feng Chen, 2020. "Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis," IJERPH, MDPI, vol. 17(8), pages 1-15, April.
    5. Xiaojun Shao & Xiaoxiang Ma & Feng Chen & Mingtao Song & Xiaodong Pan & Kesi You, 2020. "A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions," IJERPH, MDPI, vol. 17(2), pages 1-18, January.
    6. Najah Al-Garawi & Muhammad Abubakar Dalhat & Omer Aga, 2021. "Assessing the Road Traffic Crashes among Novice Female Drivers in Saudi Arabia," Sustainability, MDPI, vol. 13(15), pages 1-11, August.
    7. Yingying Xing & Shengdi Chen & Shengxue Zhu & Yi Zhang & Jian Lu, 2020. "Exploring Risk Factors Contributing to the Severity of Hazardous Material Transportation Accidents in China," IJERPH, MDPI, vol. 17(4), pages 1-19, February.
    8. Changxi Ma & Jibiao Zhou & Dong Yang, 2020. "Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model," IJERPH, MDPI, vol. 17(4), pages 1-25, February.
    9. Feng Chen & Mingtao Song & Xiaoxiang Ma, 2019. "Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model," IJERPH, MDPI, vol. 16(14), pages 1-12, July.
    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. Fanyu Meng & Pengpeng Xu & Cancan Song & Kun Gao & Zichu Zhou & Lili Yang, 2020. "Influential Factors Associated with Consecutive Crash Severity: A Two-Level Logistic Modeling Approach," IJERPH, MDPI, vol. 17(15), pages 1-16, August.
    2. Haorong Peng & Xiaoxiang Ma & Feng Chen, 2020. "Examining Injury Severity of Pedestrians in Vehicle–Pedestrian Crashes at Mid-Blocks Using Path Analysis," IJERPH, MDPI, vol. 17(17), pages 1-16, August.
    3. Afaq Khattak & Hamad Almujibah & Ahmed Elamary & Caroline Mongina Matara, 2022. "Interpretable Dynamic Ensemble Selection Approach for the Prediction of Road Traffic Injury Severity: A Case Study of Pakistan’s National Highway N-5," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    4. Kanghyun Kim & Jungyeol Hong, 2023. "Severity Predictions for Intercity Bus Crashes on Highway Using a Random Parameter Ordered Probit Model," Sustainability, MDPI, vol. 15(17), pages 1-15, August.
    5. Ming Sun & Ronggui Zhou, 2023. "Investigation on Hazardous Material Truck Involved Fatal Crashes Using Cluster Correspondence Analysis," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    6. Sheng Dong & Afaq Khattak & Irfan Ullah & Jibiao Zhou & Arshad Hussain, 2022. "Predicting and Analyzing Road Traffic Injury Severity Using Boosting-Based Ensemble Learning Models with SHAPley Additive exPlanations," IJERPH, MDPI, vol. 19(5), pages 1-23, March.
    7. Ming Lv & Xiaojun Shao & Chimou Li & Feng Chen, 2022. "Driving Performance Evaluation of Shuttle Buses: A Case Study of Hong Kong–Zhuhai–Macau Bridge," IJERPH, MDPI, vol. 19(3), pages 1-13, January.
    8. Zhi Zhang & Yingshi Guo & Rui Fu & Wei Yuan & Chang Wang, 2020. "Linking executive functions to distracted driving, does it differ between young and mature drivers?," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-12, September.
    9. Li Zhou & Chun Guo & Yunxiao Cui & Jianjun Wu & Ying Lv & Zhiping Du, 2020. "Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management," IJERPH, MDPI, vol. 17(8), pages 1-24, April.
    10. Ming Sun & Ronggui Zhou & Chengwu Jiao & Xiaoduan Sun, 2022. "Severity Analysis of Hazardous Material Road Transportation Crashes with a Bayesian Network Using Highway Safety Information System Data," IJERPH, MDPI, vol. 19(7), pages 1-22, March.
    11. Zhuanglin Ma & Mingjie Luo & Steven I-Jy Chien & Dawei Hu & Xue Zhao, 2020. "Analyzing drivers’ perceived service quality of variable message signs (VMS)," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-19, October.
    12. Hamed, Mohammad M. & Mohammed, Ali & Olabi, Abdul Ghani, 2023. "Renewable energy adoption decisions in Jordan's industrial sector: Statistical analysis with unobserved heterogeneity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    13. Changxi Ma & Jibiao Zhou & Dong Yang, 2020. "Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model," IJERPH, MDPI, vol. 17(4), pages 1-25, February.
    14. Zheng Chen & Huiying Wen & Qiang Zhu & Sheng Zhao, 2023. "Severity Analysis of Multi-Truck Crashes on Mountain Freeways Using a Mixed Logit Model," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    15. Mahyar Madarshahian & Aditya Balaram & Fahim Ahmed & Nathan Huynh & Chowdhury K. A. Siddiqui & Mark Ferguson, 2023. "Analysis of Injury Severity of Work Zone Truck-Involved Crashes in South Carolina for Interstates and Non-Interstates," Sustainability, MDPI, vol. 15(9), pages 1-18, April.
    16. Wen Cheng & Fei Ye & Changshuai Wang & Jiping Bai, 2023. "Identifying the Factors Contributing to Freeway Crash Severity Based on Discrete Choice Models," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    17. Carina Goldbach & Christin Hoffmann & Julia Hoppe & Thomas Pitz & Kirsten Thommes, 2020. "The fast and the furious—An experimental investigation of the pace of life and risky speed choice in traffic," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-20, July.
    18. Vicente Joaquín Delgado-Fernández & María del Carmen Rey-Merchán & Antonio López-Arquillos & Sang D. Choi, 2022. "Occupational Traffic Accidents among Teachers in Spain," IJERPH, MDPI, vol. 19(9), pages 1-9, April.
    19. Xiuguang Song & Rendong Pi & Yu Zhang & Jianqing Wu & Yuhuan Dong & Han Zhang & Xinyuan Zhu, 2021. "Determinants and Prediction of Injury Severities in Multi-Vehicle-Involved Crashes," IJERPH, MDPI, vol. 18(10), pages 1-16, May.
    20. Chen, Jiangfan & Fang, Zheng & Azam, Ali & Wu, Xiaoping & Zhang, Zutao & Lu, Linhai & Li, Dongyang, 2023. "An energy self-circulation system based on the wearable thermoelectric harvester for ART driver monitoring," Energy, Elsevier, vol. 262(PA).

    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:jijerp:v:18:y:2021:i:23:p:12725-:d:693610. 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.