IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p6499-d1121027.html
   My bibliography  Save this article

Severity Analysis of Multi-Truck Crashes on Mountain Freeways Using a Mixed Logit Model

Author

Listed:
  • Zheng Chen

    (School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China)

  • Huiying Wen

    (School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China)

  • Qiang Zhu

    (Guangzhou City District Transportation Project Management Center, Guangzhou 510030, China)

  • Sheng Zhao

    (School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China)

Abstract

Many studies have analyzed the road characteristics that affect the severity of truck crashes. However, most of these studies have only examined road alignment or grade separately, without considering their combined effects. The purpose of this article is to address this gap in the literature. Our study uses truck crash data from 2015 to 2019 on freeways in the Yunnan Province of China, where the severity levels of the crashes were determined by taking into account economic loss and the number of injuries and fatalities. Our study develops three models to examine the severity of truck crashes: a multinomial logit model, a mixed logit model, and a generalized ordered logit model. The findings suggest that the mixed logit model, which can suffer from unobserved heterogeneity, is more suitable because of the higher pseudo-R-squared ( ρ 2 ) value and lower Akaike Information Criterion and Bayesian Information Criterion. The estimation results show that the combination of curve and slope significantly increases the severity of truck crashes compared to curves and slopes alone. In addition, risk factors such as crash type, vehicle type, surface condition, time of day, pavement structure, and guardrails have a significant impact on the severity of truck crashes on mountainous freeways. Based on these findings, we developed policy recommendations for reducing the severity of multi-truck collisions on mountainous highways and improving transport sustainability. For example, if possible, the combination of curve and slope should be avoided. Additionally, it is recommended that trucks use tires with good heat resistance.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6499-:d:1121027
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/6499/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/8/6499/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ziyuan Qi & Jingmeng Yao & Xuan Zou & Kairui Pu & Wenwen Qin & Wu Li, 2024. "Investigating Factors Influencing Crash Severity on Mountainous Two-Lane Roads: Machine Learning Versus Statistical Models," Sustainability, MDPI, vol. 16(18), pages 1-27, September.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Milad Delavary Foroutaghe & Abolfazl Mohammadzadeh Moghaddam & Vahid Fakoor, 2020. "Impact of law enforcement and increased traffic fines policy on road traffic fatality, injuries and offenses in Iran: Interrupted time series analysis," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-13, April.
    9. 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.
    10. 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.
    11. 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.
    12. Yubing Zheng & Yang Ma & Nan Li & Jianchuan Cheng, 2019. "Personality and Behavioral Predictors of Cyclist Involvement in Crash-Related Conditions," IJERPH, MDPI, vol. 16(24), pages 1-19, December.
    13. Seung-Hoon Park & Min-Kyung Bae, 2020. "Exploring the Determinants of the Severity of Pedestrian Injuries by Pedestrian Age: A Case Study of Daegu Metropolitan City, South Korea," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    14. 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.
    15. Yun Xiao, 2020. "Analysis of the influencing factors of the unsafe driving behaviors of online car-hailing drivers in china," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-13, April.
    16. 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.
    17. Jinhua Tan & Li Gong & Xuqian Qin, 2019. "Effect of Imitation Phenomenon on Two-Lane Traffic Safety in Fog Weather," IJERPH, MDPI, vol. 16(19), pages 1-15, October.
    18. Mostafa Sharafeldin & Ahmed Farid & Khaled Ksaibati, 2022. "Injury Severity Analysis of Rear-End Crashes at Signalized Intersections," Sustainability, MDPI, vol. 14(21), pages 1-14, October.
    19. Zijun Liang & Yun Xiao, 2020. "Analysis of factors influencing expressway speeding behavior in China," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-13, September.
    20. Yongji Ma & Jinliang Xu & Chao Gao & Minghao Mu & Guangxun E & Chenwei Gu, 2022. "Review of Research on Road Traffic Operation Risk Prevention and Control," IJERPH, MDPI, vol. 19(19), pages 1-26, September.

    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:jsusta:v:15:y:2023:i:8:p:6499-:d:1121027. 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.