Driving in tunnel areas depends more heavily on light conditions than that on open roadways. Traditional lighting systems in highway tunnels adjust lighting parameters only caring about outside light luminance, and focus is usually on energy conservation; however, little concern is about drivers’ actual physical and psychological needs. How to leverage the enormous research progress of traffic safety, light environment, human factors engineering, and modern lighting sources to create an ideal tunnel light environment that aids with ensuring driving safety and lower interference effects caused by the change of light environment will greatly improve safety level and reduce adverse influence on drivers’ visual health in a tunnel area. An intelligent lighting control system designed with multiple influence factors are systematically considered. Based on sensor data from outside natural light conditions, target lighting parameters are determined per each lighting zone requires; then, lighting commands will be transferred and parsed by adaptive lighting controllers and modules, eventually LED lighting properties are altered step by step. This system helps a lot with optimizing tunnel lighting quality and improving drivers’ visual performance; as a result, it contributes to lower the fluctuation of drivers’ workload and get a smooth traffic flow, and ultimately this technically ensures physical and mental health of drivers in a tunnel area.

The anti-glare facilities in median strips are designed to block opposing headlights in order to avoid disability glare, but a large amount of headlight leakage results in uncomfortable glare, to the point that drivers can barely detect dangerous obstacles or road conditions. This paper aims to explore the glare range under high-beam headlights on drivers’ visual requirements. Based on an analysis of the mechanism of headlight glare, this paper proposes a subjective headlight glare scale, and classifies glare discomfort into two categories: interference glare, and acceptability glare. Combining the scales, 24 drivers and a standard light-emitting diode automotive headlamp were used to conduct glare effect tests. The size of the laboratory that closes to scotopic vision is 12 m × 6 m. The illuminance thresholds of disability glare–interference glare (DGIG) and interference glare–acceptability glare (IGAG), along with the spatial distribution of each glare level, were collected at the longitudinal distances of 3 m, 5 m, 7 m, 10 m, and 12 m. Meanwhile, the illuminance threshold and the spatial distribution of each glare level up to a longitudinal distance of 120 m were calculated. The results indicate that disability glare is distributed in the central area, while interference glare and acceptability glare are distributed from the center to the margins. At the same longitudinal distance, the vertical illuminance of the driver’s eye under the same glare level is almost equal. In the range of a longitudinal distance of 120 m, the spatial distribution of each glare level enlarges with each increase in longitudinal distance. The results can provide scientific evidence for calculating the reasonable heights of anti-glare facilities for expressways with different alignments.

Few researches have focused on the comprehensive efficiency of tunnel lighting, which plays a role in improving the tunnel lighting efficiency. This article defined visual recognition time as the representation of visual performance. Three indices, visual performance, light efficiency, and production cost, were proposed to study the visual performance of test drivers, when drivers recognized an obstacle in LED lighting environment with different characteristics. A total of 15 light combinations were designed in the middle section of tunnel, composed by 5 color temperatures and 4 color rendering indices under 8 different kinds of light brightness. A total of 12 test drivers were selected to conduct the static recognition experiment in different lighting environments. Recognition time, lighting performance, and production cost were normalized, and K-means clustering was applied to analyze these indices to obtain the values of comprehensive efficiency of LED with different characteristics. The results indicated that increasing the light color rendering can improve the visibility without increasing the light power. The following combinations of color temperature with color rendering, 6500 K with 70, 5700 K with 70, 5700 K with 80, 3000 K with 80, 3000 K with 70, and 4000 K with 70, performed better comprehensive efficiency, showing better visual performance, higher light efficiency, and lower production cost.

The tunnel is an important component of freeway operation safety, and its classification method is the foundation of a refined management of operation safety. At present, the impact of different categories of tunnels on driver safety, comfort, and driving behavior under naturalistic driving conditions is not clear, and there is a lack of classification methods for tunnels of different lengths in their operation stages. This paper was based on the driving workload, which effectively expresses the safety and comfort of drivers. In this context, naturalistic driving experiments in 13 freeways and 98 tunnels with 36 participants were carried out. The DDTW+K-Means++ algorithm, which is suitable for drivers’ driving workload time series data, was used for a clustering analysis of the tunnels. According to the length of the tunnel, the operation-stage tunnels were divided into three categories: short tunnels (4000 m). The length of the tunnel had a positive correlation with the drivers’ driving workload, while there was a negative correlation with the vehicle running speed, and the range of changes in the drivers’ driving workload and operation safety risks in general tunnels and long tunnels was higher than that in short tunnels. Road and environmental conditions are important factors affecting the driving workload. The entrance area, the exit area of tunnels, and the middle area of long tunnels are high-risk sections in the affected area of the tunnel. These research results are of great significance for the operation safety management of freeway tunnels.

Drivers’ behavior characteristics cannot be ignored in designing freeway interchange facilities in order to improve traffic safety. This paper conducted a field experiment in Qingyin expressway. Four freeway interchanges from K571+538 to K614+932 with relatively low volume were selected, and 12 qualified drivers, 6 car test drivers and 6 truck test drivers, were driving vehicles according to the driving program. GPS and eye-tracking instrument were employed to record running speed, real-time, running track, fixation point, and so forth. Box-plot graphs and Student’st-test were used to analyze the 12 data sets of driver’s fixation on exit guide signs. Speed-distance curves of effective 11 data sets were plotted to examine the test drivers’ behavior in diverging area and merging area. The results indicated that (1) drivers recognize the exit direction signs in 170 m–180 m advanced distance; (2) the diverging influence area is 1000 m upstream of the diverge point, and the merging influence area is 350 m downstream of the merge point; (3) NO OVERTAKING sign is recommended to be placed at 350 m upstream of the diverge point. The results can provide guidance for the design of freeway interchange facilities and management in order to improve traffic safety.

Significant changes in road and traffic conditions in transition areas are key to traffic organization and guaranteeing safety in freeway work zones. Currently, most of the related studies on transition area use theoretical calculations, traffic and driving simulations, and the impact of different transition area conditions on drivers’ psychophysiological indicators and driving behavior are unclear. In this paper, the gap acceptance theory was used to establish a calculation method of the transition area length, and the transition area length was calculated under different closed lane widths, speed limits, and traffic volumes. Based on the results of our theoretical calculations, naturalistic driving experiments were conducted with 48 participants in 12 scenarios involving 3 lane closure forms and 4 transition area lengths, and the relationship of transition area with driving workload and vehicle speed was determined. A transition area that was too short or too long increased traffic safety risks. The overall experimental results were consistent with the theoretical calculation length, and the theoretical calculation model was reliable. Compared to unaffected straight-through vehicles, merging vehicles and vehicles affected by merging have lower speeds, higher driving workloads, and increased traffic safety risks. An increase in the number of lanes in the transition area will result in increased driving workloads and vehicle speeds. Based on the changes in vehicle deceleration points and driving workloads, the affected area of the transition area was measured. When the speed limit was 60 km/h, the upstream affected areas of the transition areas with four, three, and two lanes were 1000 m, 850 m, and 700 m, and the downstream affected areas were 450 m, 400 m, and 350 m. These research results can provide a reference for improving traffic organization and guaranteeing safety in freeway work zones.