Driving safety risk evaluation for tunnel reinforcement based on matter-element model

Objective: This study aimed to analyze the influence of different tunnel reinforcement measures on drivers and to evaluate the associated driving safety risks.

Methods: Experimental data of driving behavior and physiological response were collected under different driving simulation scenarios, such as cover arch erection, corrugated steel, grouting, Steel strips, and fire; an evaluation index system was established based on electrocardiographic (ECG), electrodermal activity(EDA), standard deviation of speed (SDSP), Steering Entropy(SE), standard deviation of lateral position (SDLP) and other indices. The classical domain rank standard of each evaluation index was divided using K-Means algorithm, and a synthetic evaluation matter-element model was established to comprehensively evaluate and analyze the safety risks of each scenario.

Results: The results show that the highway tunnel reinforcement measures can reduce the driving safety risks compared with the severe damage scenario, and the key driving stability indices such as SDSP, SDLP, and SE are effectively improved by each reinforcement method. Different reinforcement methods have significant differences on driving safety: the cover arch erection and grouting reinforcement are more effective in reducing risks of driving safety, while corrugated steel and Steel strips feature relatively high safety risks. By synthesizing the overall safety risk levels and indices of each reinforcement method, the cover arch erection performs best in reinforcement and maintenance, followed by grouting.

Conclusion: By assessing the effects of different reinforcement methods on driving behavior, this study provides valuable insights and data support for decision-making of highway tunnel safety operation and post-disaster rehabilitation.