A dual-model approach to traffic risk assessment of mountainous expressway tunnel groups

Objective To improve the traffic risk conditions of mountainous expressway tunnel sections, it is necessary to conduct safety risk assessments and adopt different countermeasures according to the assessed risk levels.Methods An evaluation system was established with 4 primary indicators—tunnel condition, traffic characteristics, operational environment, and safety facilities—and 16 secondary indicators. Safety status was divided into 5 risk levels. To assign indicator weights objectively, information entropy was used to improve the traditional CRITIC method. Two assessment models based on extension matter-element theory and set pair analysis were then developed to form a dual-verification mechanism: the former handles indicator–grade incompatibility via correlation functions, while the latter treats assessment uncertainty using multiple connection numbers.Results Fifteen tunnels on the Guangzhou-Kunming Expressway in Yunnan Province were selected as evaluation objects. The improved CRITIC method effectively reduced subjective bias, with key indicator weights adjusted by up to 10% for more objective weighting. The extension matter-element model and set pair analysis (SPA) model yielded highly consistent dual assessment results (agreement rate >80%). Most tunnels were classified as low-risk, while several long tunnels were categorized as medium-risk. The SPA model showed greater advantages in describing risk evolution trends, clearly characterizing transitions between adjacent risk levels via potential series.Conclusion The improved CRITIC method significantly enhances the objectivity of indicator weighting, making it more consistent with actual tunnel conditions. The combined application of the extension matter-element model and the set pair analysis model form a complementary dual verification mechanism. Case studies verified that this integrated evaluation system can accurately determine tunnel safety levels and provide a reliable basis for developing targeted risk prevention and control measures.