Influence of Vehicle Speed on the Characteristics of Driver's Eye Movement at a Highway Tunnel Entrance during Day and Night Conditions: A Pilot Study

Influence of an adjacent tunnel connecting zone shading shed on drivers' eye movement characteristics

A tunnel shading shed is crucial in improving driving safety as a type of traffic facility to ease the transition of light environments. To study the effect of installation of a shading shed on the visual characteristics of drivers in the connecting zone of the adjacent tunnels, a total of 32 drivers were gathered to perform a real vehicle experiment. The study zone of the adjacent tunnels was divided into three sections: upstream tunnel exit; connecting zone; and downstream tunnel threshold zone. Fixation duration, saccade duration and saccade frequency were selected as research indexes. The results suggest that installation of a shading shed in the connecting zone significantly reduced the fixation (saccade) duration in the upstream tunnel exit and downstream tunnel threshold zones, with a significantly higher saccade frequency. In addition, fixation is better improved at the downstream tunnel entrance, and saccade is better enhanced at the upstream tunnel exit.

Online Intelligent Perception of Front Blind Area of Vehicles on a Full Bridge Based on Dynamic Configuration Monitoring of Main Girders

Establishing an online perception mechanism for a driver's front blind area on a full bridge under vertical vortex-induced vibration (VVIV) is essential for ensuring road safety and traffic control on bridge decks under specific conditions. Based on accelerations of vibration monitoring of the main girders, this paper uses a real-time acceleration integration algorithm to obtain real-time displacements of measurement points; realizes the real-time estimation of the dynamic configurations of a main girder through parametric function fitting; and then can perceive the front blind area for vehicles driving on bridges experiencing VVIV in real time. On this basis, taking a long-span suspension bridge suffering from VVIV as an engineering example, the influence of different driving conditions on the front blind area is examined. Then, the applicability of the intelligent perception technology framework of the front blind area is verified. The results indicate that, during VVIV, the driver's front blind area changes periodically and the vehicle model has the most significant impact on the front blind area; in contrast, the vehicle's speed and the times of the vehicle entering the bridge have minimal impact on it. Meanwhile, it is shown that the framework can accurately perceive front blind areas of vehicles driving on the bridge, and identify different vehicle models, speeds and times of vehicle bridge entries in real time.

Effects of the Spatial Structure Conditions of Urban Underpass Tunnels' Longitudinal Section on Drivers' Physiological and Behavioral Comfort

To investigate the physiological and behavioral comfort of drivers traversing urban underpass tunnels with various spatial structure conditions, a driving simulator experiment was conducted using 3DMAX and SCANeRTM studio software. Three parameters, including the slope, slope length, and height of a tunnel, were selected as research objects to explore the optimal combination of structural parameters in urban underpass tunnels. The heart rate (HR), interbeat (RR) interval, speed, and lane centerline offset value were collected for 30 drivers. Then, a measurement model of the relationship among HR, RR interval, speed, lane centerline offset value, and structural parameters was established by using partial correlation analyses and the stepwise regression method. On this basis, a structural constraint model based on the drivers’ physiological and behavioral comfort thresholds was also constructed. The results show that the driver’s HR, RR interval, speed, and lane centerline offsets are significantly related to the tunnel height, slope, and slope length. More importantly, this paper not only analyzed the effects of various structural parameters on drivers’ physiology and behavior but also proposed an optimized combination of structural parameters based on drivers’ physiological and behavioral comfort. It can reasonably improve tunnel design in China, ensure tunnel traffic safety, and seek the maximum comfort of the driver in the driving process.

Analysis of EEG Characteristics of Drivers and Driving Safety in Undersea Tunnel

To study the influence of the driving environment of an undersea tunnel on driver EEG (electroencephalography) characteristics and driving safety, a real vehicle experiment was performed in the Qingdao Jiaozhou Bay Tunnel. The experimental data of the drivers’ real vehicle experiment were collected using an illuminance meter, EEG instrument, video recorder and other experimental equipment. The undersea tunnel is divided into different areas, and the distribution law of driving environment characteristics, EEG characteristics and vehicle speed characteristics is analyzed. The correlations between the driving environment characteristics, EEG characteristics and vehicle speed characteristics model the variables that pass the correlation test. The driving safety evaluation model of an undersea tunnel is established, and the driving safety in different areas of the undersea tunnel is evaluated. The results show that there are obvious differences in illumination, EEG power change rate, vehicle speed and other variables in different areas of the undersea tunnel. The driving environment characteristics are highly correlated with the β wave power change rate. The driving safety of different areas of the undersea tunnel from high to low is: upslope area, downslope area, exit area and entrance area. The study will provide a theoretical basis for the safe operation of the undersea tunnel.

Use of Pupil Area and Fixation Maps to Evaluate Visual Behavior of Drivers inside Tunnels at Different Luminance Levels—A Pilot Study

This study reports the results of a pilot study on spatiotemporal characteristics of drivers’ visual behavior while driving in three different luminance levels in a tunnel. The study was carried out in a relatively long tunnel during the daytime. Six experienced drivers were recruited to participate in the driving experiment. Experimental data of pupil area and fixation point position (at the tunnel’s interior zone: 1566 m long) were collected by non-intrusive eye-tracking equipment at three luminance levels (2 cd/m2, 2.5 cd/m2, and 3 cd/m2). Fixation maps (color-coded maps presenting distributed data) were created based on fixation point position data to quantify changes in visual behavior. The results demonstrated that luminance levels had a significant effect on pupil areas and fixation zones. Fixation area and average pupil area had a significant negative correlation with luminance levels during the daytime. In addition, drivers concentrated more on the front road pavement, the top wall surface, and the cars’ control wheels. The results revealed that the pupil area had a linear relationship with the luminance level. The limitations of this research are pointed out and the future research directions are also prospected.

Change-Point Analysis of Eye Movement Characteristics for Female Drivers in Anxiety

Driver hazard perception is highly related to involvement in traffic accidents, and vision is the most important sense with which we perceive risk. Therefore, it is of great significance to explore the characteristics of drivers' eye movements to promote road safety. This study focuses on analyzing the changes of drivers' eye-movement characteristics in anxiety. We used various materials to induce drivers' anxiety, and then conducted the real driving experiments and driving simulations to collect drivers' eye-movement data. Then, we compared the differences between calm and anxiety on drivers' eye-movement characteristics, in order to extract the key eye-movement features. The least squares method of change point analysis was carried out to detect the time and locations of sudden changes in eye movement characteristics. The results show that the least squares method is effective for identifying eye-movement changes of female drivers in anxiety. It was also found that changes in road environments could cause a significant increase in fixation count and fixation duration for female drivers, such as in scenes with traffic accidents or sharp curves. The findings of this study can be used to recognize unexpected events in road environment and improve the geometric design of curved roads. This study can also be used to develop active driving warning systems and intelligent human⁻machine interactions in vehicles. This study would be of great theoretical significance and application value for improving road traffic safety.