Multi-dimensional coupling study on traffic accident risk in Tiantai Mountain Tunnel Cluster, China

To address the impacts of the coupling of multiple risk factors on the safe operation of the Tiantai Mountain Tunnel Cluster (MTC) in the Qinling mountains, China, key risk factors were identified and controlled to improve the safety risk management of the tunnel and reduce the traffic accident (TA) rate. TA data for the MTC from 2021 to 2024 were obtained and five level-1 and 23 level-2 risk factors affecting tunnel safety were identified. The level-1 risk factors were found to be people, vehicle, road, environment and management. An integrated model of analytic hierarchy process (AHP), the N–K model (NKM) and social network analysis (SNA) was used to form a new risk coupled analysis framework. The NKM evaluated coupling in TA cases, while the AHP model generated a risk matrix that was visualised through SNA, focusing on centrality, accessibility and cohesive subgroups. The results showed that, the larger the number of risk factors involved, the higher the risk coupling value and the greater the TA risk. Notably, risks taken by drivers was found to contribute to stronger multi-risk coupling involving ‘people–vehicle–environment’. Key factors identified include safety management systems as well as adverse weather conditions. These insights highlight critical risk factors and provide a basis for improved decision making regarding traffic safety.