Freeway Tunnel Driving Risk Assessment: Combining Feature Dimensionality Reduction and Driving Style Classification

Driving risk assessment in tunnels is not only fundamental for evaluating traffic safety but also a critical prerequisite for analyzing and understanding the formation mechanisms of vehicle operational risks. Based on naturalistic driving trajectory data of the Xiaxiyao tunnel of Wuyu freeway from the Tongji Road Trajectory Sharing Platform (TJRD TS), this study extracts 19 driving behavior parameters and classifies drivers into four categories using the PCA-K-medoids method: conservative, moderate, aggressive-a, and aggressive-b. Considering six dimensions (safety speed difference, driving instability, time headway, acceleration, speed difference, and acceleration difference), the driving risk assessment model of the freeway tunnel is constructed by determining the weight by the entropy weight-CRITIC method. The model analyzes the risk evolution of different driver types during travel. The results indicate that conservative and moderate drivers typically maintain larger time headways and following distances. The proportions of these drivers whose peak risk values remain at no risk or low risk level are 85.95% and 76.79%, respectively. Regarding driving risks in different zones, aggressive-a drivers exhibit higher risk levels from 400 m before the tunnel exit to 300 m after the exit, whereas aggressive-b drivers demonstrate an increased risk propensity from 200 m before the entrance and 300 m after the entrance. Further behavioral analysis highlights that aggressive-a drivers exhibit higher acceleration, maximum speed, and speed differences with leading vehicles, and aggressive-b drivers demonstrate higher deceleration. During speeding, aggressive-b drivers show the highest average driving risk index (0.28), with 65.34% of cases classified as medium- or high-risk. Under low-speed conditions, aggressive-a and aggressive-b drivers exhibit medium- or high-risk proportions of 62.16% and 57.67%, respectively. Compared with moderate drivers, aggressive-a drivers experience a 22.7% increase in average driving risk index during rapid acceleration, whereas aggressive-b drivers show a 15.4% increase. The probability of aggressive-a and aggressive-drivers being at moderate and high risk levels in the car-following conditions was 58.41% and 63.74%, respectively. This study reveals the risk characteristics of different driving styles in tunnels, providing valuable insights for precise vehicle management, hazard mitigation, and proactive safety governance in tunnel environments.