Computation model of safety index for mountainous expressway accident-prone sections.

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Bibliographic Details
Title:	Computation model of safety index for mountainous expressway accident-prone sections.
Authors:	Meng, Y.¹ ywmeng@cqjtu.edu.cn, Zhang, J.², Zhang, Y.³, Liu, Z.⁴, Qing, G.⁵
Source:	Advances in Transportation Studies. Apr2026, Vol. 68, p277-294. 18p.
Subjects:	Safety, Road safety measures, Express highways, Quantitative research, Traffic engineering, Statistics
Abstract:	Accident-prone sections on mountainous expressways pose heightened risks due to complex terrain and alignment conditions. Quantitative evaluation of their safety levels is essential for prioritizing remedial measures and enhancing traffic management strategies. This study introduces the concept of a safety index for special sections and establishes a quantitative model. Five core factors--accident index, operating speed, alignment, road friction variation, and terrain--were selected. These indicators were weighted using CRITIC and integrated into a cloud model constructed through a positive normal cloud generator. The model accounted for the differential contributions of each factor across road sections and generated membership values that enabled accurate safety classification. The results identified clear differences among sections and provided a reliable basis for prioritizing interventions. The proposed model offers a practical decision-support tool for traffic management and construction authorities. It enables the identification and ranking of accident-prone sections, and it facilitates quantitative evaluation of intervention effectiveness before and after treatment, thereby supporting proactive safety management on mountainous expressways. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Accident-prone sections on mountainous expressways pose heightened risks due to complex terrain and alignment conditions. Quantitative evaluation of their safety levels is essential for prioritizing remedial measures and enhancing traffic management strategies. This study introduces the concept of a safety index for special sections and establishes a quantitative model. Five core factors--accident index, operating speed, alignment, road friction variation, and terrain--were selected. These indicators were weighted using CRITIC and integrated into a cloud model constructed through a positive normal cloud generator. The model accounted for the differential contributions of each factor across road sections and generated membership values that enabled accurate safety classification. The results identified clear differences among sections and provided a reliable basis for prioritizing interventions. The proposed model offers a practical decision-support tool for traffic management and construction authorities. It enables the identification and ranking of accident-prone sections, and it facilitates quantitative evaluation of intervention effectiveness before and after treatment, thereby supporting proactive safety management on mountainous expressways. [ABSTRACT FROM AUTHOR]
ISSN:	18245463
DOI:	10.53136/979122182541117