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Study on Full-Process Risk Identification and Assessment System for Highway Abnormal Indivisible Load Transport

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Listed:
  • Wang, Daiyue
  • Xiao, Jian
  • Li, Pengfei
  • Dai, Shuangliang
  • Liu, Wangtao
  • Wang, Yixu
  • Wang, Jianbo

Abstract

As a key logistics support for the construction of national key engineering projects, highway abnormal indivisible load transport (HAILT) entails significantly higher safety risks than ordinary freight due to its special cargo structure, complex transport routes, and numerous collaborative links. This study aims to construct a systematic, full-process risk identification and assessment system for HAILT. By systematically identifying risk sources throughout the entire HAILT process, these sources are classified into five categories: personnel risks, cargo risks, transport equipment risks, route condition risks, and management risks. Furthermore, a risk assessment method integrating qualitative and quantitative analysis is proposed, which employs a risk matrix model to quantify risk levels and accordingly formulates differentiated risk control strategies. This system provides a theoretical framework and practical pathway for realizing advanced identification, scientific evaluation, and precise control of HAILT risks, and holds important reference value for improving the overall safety management level of the industry.

Suggested Citation

  • Wang, Daiyue & Xiao, Jian & Li, Pengfei & Dai, Shuangliang & Liu, Wangtao & Wang, Yixu & Wang, Jianbo, 2025. "Study on Full-Process Risk Identification and Assessment System for Highway Abnormal Indivisible Load Transport," GBP Proceedings Series, Scientific Open Access Publishing, vol. 15, pages 229-244.
    • Handle: RePEc:axf:gbppsa:v:15:y:2025:i::p:229-244
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