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

Area of Science:

• Civil Engineering
• Transportation Engineering
• Human Factors Engineering

Background:

• Highway tunnel integrity is crucial for safe transportation.
• Tunnel damage necessitates effective reinforcement to mitigate risks.
• Driver behavior and physiological responses are key indicators of safety.

Purpose of the Study:

• To analyze the impact of various tunnel reinforcement techniques on driver behavior.
• To evaluate the driving safety risks associated with different reinforcement methods.
• To provide data for optimizing tunnel safety and post-disaster recovery.

Main Methods:

• Driving simulation experiments collected data on driver behavior and physiological responses.
• Evaluation indices included electrocardiographic (ECG), electrodermal activity (EDA), standard deviation of speed (SDSP), Steering Entropy (SE), and standard deviation of lateral position (SDLP).
• K-Means algorithm and a synthetic evaluation matter-element model were used to assess safety risks.

Main Results:

• All tested reinforcement measures reduced driving safety risks compared to severe damage scenarios.
• Reinforcement methods improved key driving stability indices: SDSP, SDLP, and SE.
• Cover arch erection and grouting were most effective in reducing risks; corrugated steel and steel strips presented higher risks.

Conclusions:

• Cover arch erection demonstrated the best performance in tunnel reinforcement and maintenance.
• Grouting reinforcement also proved effective, offering significant safety improvements.
• Findings support informed decision-making for highway tunnel safety operations and rehabilitation efforts.