Tunnels are vital in connecting crucial transportation hubs as transportation infrastructure evolves.Variations in tunnel design standards and driving conditions across different levels directly impact driver visual p...Tunnels are vital in connecting crucial transportation hubs as transportation infrastructure evolves.Variations in tunnel design standards and driving conditions across different levels directly impact driver visual perception and traffic safety.This study employs a Gaussian hybrid clustering machine learning model to explore driver gaze patterns in highway tunnels and exits.By utilizing contour coefficients,the optimal number of classification clusters is determined.Analysis of driver visual behavior across tunnel levels,focusing on gaze point distribution,gaze duration,and sweep speed,was conducted.Findings indicate freeway tunnel exits exhibit three distinct fixation point categories aligning with Gaussian distribution,while highway tunnels display four such characteristics.Notably,in both tunnel types,65%of driver gaze is concentrated on the near area ahead of their lane.Differences emerge in highway tunnels due to oncoming traffic,leading to 13.47%more fixation points and 0.9%increased fixation time in the right lane compared to regular highway tunnel conditions.Moreover,scanning speeds predominantly fall within the 0.25-0.3 range,accounting for 75.47%and 31.14%of the total sweep speed.展开更多
Highway tunnel entrances have a high rate of expressway traffic accidents.In this paper,the reasons for the high incidence of traffic accidents at highway tunnel entrances are analyzed in detail,and corresponding solu...Highway tunnel entrances have a high rate of expressway traffic accidents.In this paper,the reasons for the high incidence of traffic accidents at highway tunnel entrances are analyzed in detail,and corresponding solutions are proposed,hoping to provide some reference to relevant parties.展开更多
基金supported by the National Natural Science Foundation of China(52302437)the Cangzhou Science and Technology Plan Project(213101011)+1 种基金the Science and Technology Program Projects of Shandong Provincial Department of Transportation(2024B28)the Doctoral Scientific Research Start-up Foundation of Shandong University of Technology(422049).
文摘Tunnels are vital in connecting crucial transportation hubs as transportation infrastructure evolves.Variations in tunnel design standards and driving conditions across different levels directly impact driver visual perception and traffic safety.This study employs a Gaussian hybrid clustering machine learning model to explore driver gaze patterns in highway tunnels and exits.By utilizing contour coefficients,the optimal number of classification clusters is determined.Analysis of driver visual behavior across tunnel levels,focusing on gaze point distribution,gaze duration,and sweep speed,was conducted.Findings indicate freeway tunnel exits exhibit three distinct fixation point categories aligning with Gaussian distribution,while highway tunnels display four such characteristics.Notably,in both tunnel types,65%of driver gaze is concentrated on the near area ahead of their lane.Differences emerge in highway tunnels due to oncoming traffic,leading to 13.47%more fixation points and 0.9%increased fixation time in the right lane compared to regular highway tunnel conditions.Moreover,scanning speeds predominantly fall within the 0.25-0.3 range,accounting for 75.47%and 31.14%of the total sweep speed.
文摘Highway tunnel entrances have a high rate of expressway traffic accidents.In this paper,the reasons for the high incidence of traffic accidents at highway tunnel entrances are analyzed in detail,and corresponding solutions are proposed,hoping to provide some reference to relevant parties.