Research on the Effect of Hazard Visibility on Drivers’ Avoidance Behavior and Discriminant Model

To investigate the effects of hazard visibility on drivers’ avoidance behaviors and safety risks, this study developed driving scenarios involving overt and covert hazards using a high-fidelity driving simulator and conducted a series of driving experiments. A linear mixed model (LMM) was employed to systematically examine the variations in vehicle kinematic characteristics, operational response behaviors, and collision risks under different hazard visibility conditions. Furthermore, a driver avoidance capability classification model was developed by integrating factor analysis with Bayesian linear discriminant analysis. The results showed that hazard visibility was a critical factor influencing drivers’ responses. Compared with overt hazards, covert hazards significantly reduced time to collision (TTC) and increased the maximum braking pedal force of the driver. The driver avoidance capability classification model achieved an accuracy of 85.8%, enabling effective identification of drivers with low, medium, and high avoidance capabilities. These findings provide insights into driver avoidance behavior and may support driver safety assessment and traffic safety education, with potential implications for reducing crash-related injuries and economic losses, as well as promoting the sustainable development of transportation.