IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i17p7820-d1738052.html
   My bibliography  Save this article

Analysis of Factors Influencing Driving Safety at Typical Curve Sections of Tibet Plateau Mountainous Areas Based on Explainability-Oriented Dynamic Ensemble Learning Strategy

Author

Listed:
  • Xinhang Wu

    (School of Engineering, Xizang University, Lhasa 850000, China
    Plateau Major Infrastructure Smart Construction and Resilience Safety Technology Innovation Center, Lhasa 850000, China)

  • Fei Chen

    (Intelligent Transport System Research Center, Southeast University, Nanjing 211189, China)

  • Wu Bo

    (School of Engineering, Xizang University, Lhasa 850000, China
    Plateau Major Infrastructure Smart Construction and Resilience Safety Technology Innovation Center, Lhasa 850000, China
    Intelligent Transport System Research Center, Southeast University, Nanjing 211189, China)

  • Yicheng Shuai

    (School of Engineering, Xizang University, Lhasa 850000, China
    Plateau Major Infrastructure Smart Construction and Resilience Safety Technology Innovation Center, Lhasa 850000, China)

  • Xue Zhang

    (School of Engineering, Xizang University, Lhasa 850000, China
    Plateau Major Infrastructure Smart Construction and Resilience Safety Technology Innovation Center, Lhasa 850000, China)

  • Wa Da

    (School of Engineering, Xizang University, Lhasa 850000, China
    Plateau Major Infrastructure Smart Construction and Resilience Safety Technology Innovation Center, Lhasa 850000, China)

  • Huijing Liu

    (School of Engineering, Xizang University, Lhasa 850000, China
    Plateau Major Infrastructure Smart Construction and Resilience Safety Technology Innovation Center, Lhasa 850000, China)

  • Junhao Chen

    (School of Engineering, Xizang University, Lhasa 850000, China
    Plateau Major Infrastructure Smart Construction and Resilience Safety Technology Innovation Center, Lhasa 850000, China)

Abstract

The complex topography of China’s Tibetan Plateau mountainous roads, characterized by diverse curve types and frequent traffic accidents, significantly impacts the safety and sustainability of the transportation system. To enhance driving safety on these mountain roads and promote low-carbon, resilient transportation development, this study investigates the mechanisms through which different curve types affect driving safety and proposes optimization strategies based on interpretable machine learning methods. Focusing on three typical curve types in plateau regions, drone high-altitude photography was employed to capture footage of three specific curves along China’s National Highway G318. Oblique photography was utilized to acquire road environment information, from which 11 data indicators were extracted. Subsequently, 8 indicators, including cornering preference and vehicle type, were designated as explanatory variables, the curve type indicator was set as the dependent variable, and the remaining indicators were established as safety assessment indicators. Linear models (logistic regression, ridge regression) and non-linear models (Random Forest, LightGBM, XGBoost) were used to conduct model comparison and factor analysis. Ultimately, three non-linear models were selected, employing an explainability-oriented dynamic ensemble learning strategy (X-DEL) to evaluate the three curve types. The results indicate that non-linear models outperform linear models in terms of accuracy and scene adaptability. The explainability-oriented dynamic ensemble learning strategy (X-DEL) is beneficial for the construction of driving safety models and factor analysis on Tibetan Plateau mountainous roads. Furthermore, the contribution of indicators to driving safety varies across different curve types. This research not only deepens the scientific understanding of safety issues on plateau mountainous roads but, more importantly, its proposed solutions directly contribute to building safer, more efficient, and environmentally friendly transportation systems, thereby providing crucial impetus for sustainable transportation and high-quality regional development in the Tibetan Plateau.

Suggested Citation

  • Xinhang Wu & Fei Chen & Wu Bo & Yicheng Shuai & Xue Zhang & Wa Da & Huijing Liu & Junhao Chen, 2025. "Analysis of Factors Influencing Driving Safety at Typical Curve Sections of Tibet Plateau Mountainous Areas Based on Explainability-Oriented Dynamic Ensemble Learning Strategy," Sustainability, MDPI, vol. 17(17), pages 1-28, August.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:17:p:7820-:d:1738052
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/17/7820/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/17/7820/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:17:y:2025:i:17:p:7820-:d:1738052. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.