An introduction to tunnel lighting: Basis, calculations, and future lines in the interface between safety and sustainability

To address the issue of excessive energy consumption in traditional lighting control systems, this study proposes a segmented dynamic tunnel lighting (SDTL) control system based on a fuzzy neural network (FNN) optimized by the sparrow search algorithm (SSA). When sensors detect a vehicle entering the tunnel, the SSA-FNN model dynamically predicts the required luminance for six tunnel segments including threshold zone one (TH1), threshold zone two (TH2), transition zone (TR), interior zone (IN), exit zone one (EX1) and exit zone two (EX2), by integrating real-time data on tunnel exterior luminance, vehicle speed and traffic volume. If no vehicles are present in the tunnel or within a specific tunnel segment, the lighting control system adjusts the luminaires in that segment to their base illumination power. Experimental results demonstrate that the proposed SDTL system achieves an overall energy-saving rate of 71.5%, outperforming the traditional dynamic tunnel lighting system at 58.0% and the manual segmented tunnel lighting system at 47.9%. Key findings include: (1) lighting demand in the TH1 and TH2 segments is predominantly influenced by exterior luminance in a tunnel, whereas in the segment, it is more sensitive to traffic volume and vehicle speed; and (2) due to the higher lighting requirements caused by the ‘black hole effect’, the energy-saving performance in the TH1, TH2 and TR segments is relatively lower compared to the IN, EX1 and EX2 segments. These insights provide valuable guidance for optimizing tunnel lighting strategies through zone-specific adaptive control, contributing to the development of sustainable transportation infrastructure.

Dynamic assessment of situation awareness in road tunnels: Considering tunnel light environment characteristics and drivers’ physiological perception states

Objective This study aims to reveal the spatial distribution characteristics of driving risks in two-lane mountainous highway tunnels, with a particular focus on the influence of different tunnel lengths on risk levels, thereby contributing to improved tunnel operational safety. Methods Field driving tests were conducted in 21 short, medium, and long tunnels located on two-lane highways in Chongqing, China. Multisource data were collected from 27 drivers, including heart rate growth rate, speed, illuminance change rate, and alignment complexity indices. The entropy-weighted method was used to determine the weights of various risk evaluation indicators, which were then integrated into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model to compute the comprehensive risk value for each tunnel. Risk levels were classified into low, relatively high, and high using the K-means clustering algorithm to analyze spatial distribution patterns. Results The study showed that short tunnels exhibited the highest overall risk level, while long tunnels had the lowest. All three tunnel types displayed a consistent pattern, which is that entrance zones exhibited significantly higher risk than exit zones, with the lowest risk occurring in the middle segments. Specifically: (1) For short tunnels, the peak risk appeared 21 m after the entrance, with high-risk zones extending up to 144 m; (2) For medium tunnels, high-risk spans were concentrated within 50–75 m before and after the entrance, with the exit zone presenting the second-highest risk; (3) For long tunnels, the peak risk was found 2 m after the entrance, and both entrance and exit zones had significantly elevated risk. The average risk value in entrance segments was approximately 1.5 times that of the middle segments. Conclusions Driving risks in two-lane highway tunnels exhibit distinct spatial distribution characteristics, with tunnel entrances and exits being the most risk-prone zones. Short tunnels, due to the frequent transition effect, present more pronounced risks. The findings provide theoretical support for tunnel structural design optimization, speed limit, and lighting system.

Impact of tunnel lighting on traffic emissions based on VR experiment and car-following method

Purpose The monotonous lighting environment in extra-long tunnels often induces mind-wandering in drivers. To address this issue, this study explores effective strategies to optimize tunnel lighting environments by configuring various background colors and special lighting zones to enhance the alertness of young drivers and ensure driving safety. Methods A virtual driving simulator was utilized to carry out the experiment. By integrating heart rate variability (HRV) indicators with facial expression analysis technology, this study systematically investigates the effects of three background lighting colors—red, blue, and yellow (with a luminance range of 30.5–39.6 cd/m2)—under single-zone and two-zone special lighting stimulation conditions. A non-contact “physiology–behavior” coupling evaluation model based on the XGBoost algorithm is developed to enable real-time monitoring of the mind-wandering levels of young drivers (K-values), providing an alternative to traditional electrode-based detection methods. Results Two-zone special lighting stimulation significantly improved driver alertness and arousal compared to single-zone stimulation. Under red background lighting with two-zone stimulation, the LF/HF ratio decreased by 32.6% (p < 0.05), and a continuous decline in neutral facial expression scores indicated a sustained alerting effect. In contrast, blue background lighting demonstrated the best performance under single-zone stimulation, reducing the LF/HF ratio by 8.39% and suggesting a short-term stress-relief advantage. Conclusion This virtual driving simulation study revealed that red and blue background lighting exert distinct effects on mind-wandering regulation. Red light with two-zone stimulation effectively suppressed mind-wandering over time, while blue light with single-zone stimulation provided rapid physiological stress relief. In addition, a heart rate–neutral emotion coupling model was constructed, enabling non-contact mind-wandering assessment through facial expression analysis, thereby simplifying the monitoring process.

Impact of tunnel lighting on driver perception and safety in foggy conditions

Traditional approaches in tunnel lighting have been directed toward the installation of appropriate luminaires in the intermediate and transitional sections with the simple objective of diminishing the effect of delayed visual accommodation during daylight hours. Such efforts run in parallel with the target of keeping the huge electrical use at the lowest level. Nevertheless, inadequate attention has been conceded to the interior areas, whose noticeable longitude in several instances, and subsequently the duration of occupancy of the users, can produce discomfort in the majority of the tunnel or underground passageway. It is in this region where the flicker effect presents a more remarkable impact. Although such effect is in fact uncomfortable, the strategies to eliminate it efficiently have not been developed in depth and the result is still deserving, especially in terms of sustainability. The reasons for this neglect, as well as some particularities and solutions, are exposed and discussed in the present article. Specifically, it is proved that the use of sunlight can be an adequate initiative and a positive energy input into design and retrofit tunnels capable of hampering or totally avoiding such unwanted effect. The innovative tunnel geometry explained in this manuscript is not cylindrical, and it is not based in revolution forms. Thus, it prevents the appearance of such unnerving visual effects, which compromise sustainability and endanger security. We are in the position to explain how the vector field generated by the normal to the points of the novel surface displayed remains non-parallel, ensuring appropriate diffusivity and, consequently, an even distribution of radiated energy. In the same manner, the notion of the tunnel is extended from a linear system to a veritable network of galleries, which can traverse in space bi- or even three-dimensionally. Accordingly, we will offer diverse instances of junctions and splices that further enhance the permeability into the terrain, augmenting the resilience capabilities of this disruptive technology. With all the former, a net reduction of costs reaching 25% can be easily expected with revenues.

The Indian railway tunnel lighting systems consume tremendous energy due to all the LEDs inside the tunnel being in the ‘ON’ state around the clock. In reality, the LEDs should only be in the ‘ON’ state when the railway passes through the tunnel. According to a survey, the average railway traffic through the tunnel is about 8 hours per day, with the remaining 16 hours being traffic-free. Most of the energy is wasted during this period. The proposed system aims to automate and control tunnel lighting using cloud and geofencing technologies. It can help reduce energy consumption while maintaining safety and lowering LED replacement costs. The system is built on a cloud-based platform and includes various components such as sensors, software, and hardware. These advanced technologies can improve the efficiency of railway infrastructure, reduce energy consumption, and decrease overall costs annually. An analysis of the first 51 tunnels indicated that current energy usage is 76.10 GW, with electricity costs approximately ₹1266.41 million. Implementing an automatic system could reduce energy consumption to 15.86 GW, lowering costs to ₹264.27 million. Energy conservation has a significant societal impact and helps bridge the gap between electricity generation and utilization.

Relationship between Average Road Surface Luminance and Overall Uniformity of Road Surface Luminance in Tunnel Lighting—Characteristics of Young and Elderly Observers—

Dynamic control of tunnel lighting

Purpose To address driver fatigue caused by the monotonous visual environment in long tunnels in mountainous areas, this study aims to investigate the effect of tunnel alert segment lighting (red, blue, yellow, and white) on alleviating driver physiological fatigue and enhancing alertness and provide theoretical and empirical evidence for the optimal design of tunnel lighting. Methods A driving simulation test was conducted to simulate a long tunnel environment. Four background luminous colors (red, blue, yellow, and white) were tested. Drivers’ physiological indicators (HRV) and Karolinska Sleepiness Scale (KSS) were recorded. The HRV indicators changes under each lighting condition were analyzed using the non-parametric Wilcoxon test to quantitatively assess the effects of the lighting colors on physiological fatigue reduction and alertness enhancement. Results The driving simulation test revealed that blue background light significantly enhanced driver alertness, followed by red and yellow background lights, which showed the second most pronounced effects. In contrast, white background light did not significantly improve fatigue indicators. The highest levels of fatigue were observed in the non-alert zone of the tunnel, highlighting the necessity for background color interventions. Conclusion Blue background light proved to be the most effective in alleviating driver fatigue in the alert zones of long tunnels. Therefore, it is recommended that blue background light be prioritized in tunnel safety lighting design. The study provides scientific evidence for optimizing human factors in tunnel lighting environments. Future research should verify the long-term effectiveness of these interventions in real-world road conditions.

Highway tunnel lighting working 24 h a day, 365 days a year largely enables traffic safety but consumes a large amount of electric energy. Moreover, these tunnel lighting installations are powered by lithium-based batteries, which rely on Li sources and flammable organic electrolytes, leading to safety and space issues, or by electric power grids facing geographic limitations and high operating costs. Thus, taking advantage of cement-based materials to create low-cost and high-safety aqueous structural batteries and further develop a self-driven tunnel-lighting system is greatly desirable. Herein, the cement-based aqueous Ni-Zn structural batteries (CNZSBs), solar panels, and LEDs are successfully assembled together to realize a fully solar-powered uninterrupted lighting system, in which the CNZSBs can deliver a maximum energy density of 2.56 kWh m-3, as well as enough compressive strength to act as part of the tunnel structure. Specifically, the solar panels featuring a sustainable energy input can enable the charging of CNZSBs for energy storage and provide stable energy for LEDs during the day, while the fully-charged CNZSBs offer a steady output voltage for lighting at night. Such an uninterrupted lighting system provides exciting opportunities for developing energy storage in building materials and exploiting renewable energy sources.

Experimental Tests of Barrier Type and Tunnel Lighting on Use of Road Passages by Three Turtle Species

Anomalous reflection and tunneling contributions of the high-frequency forward light scattering by non-absorbing spheres are modeled by the scalar diffraction of two complex annuli-one for TM and TE polarizations. Their complex radii, which depend on the refractive indices and particle size, are derived from the complex angular momentum (CAM) method, thus suggesting possible extensions to non-electromagnetic scattering. Coupled with the diffraction of a disk, and a geometrical optics approximation (GOA) for the refractive contributions, we propose an accurate hybrid model that requires one to two orders of magnitude less computational time than the Lorenz-Mie theory (LMT) in the near field, a crucial improvement for, e.g., inverse methods.

Evaluating the effectiveness of rhythmic visual guidance technology for mitigating driving risks in highway tunnel groups: A simulation study.

ABSTRACT The complex tunnel lighting condition affects the image-capturing process, leading to motion blurs affecting the segmentation accuracy for tunnel leakage objects. To address the abovementioned limitations, a novel two-phase segmentation method for blurry images involving the SRN-DeblurNet and the improved YOLO v8 segmentation network is proposed. The corresponding deblurred images are restored based on the multi-scale features of blurry images. Subsequently, the leakage features are extracted from the deblurred images, and the segmentation masks are predicted. The dataset construction processes are designed to train the proposed method step by step. The motion blur patterns of tunnel images are proposed to generate training and test images. After the deblurring process, the clarity improvements of the tunnel lining images are analyzed, while the quality change is discussed. The deblurred images are segmented by the improved YOLO v8 segmentation network, and the results of YOLO v8 on test datasets are illustrated. By comparing the segmentation results of blurry and deblurred images, the effectiveness of the proposed method is analyzed in detail. Ablation studies are conducted to evaluate the trainability and the efficiency of the proposed method. Results present the effectiveness of the proposed method in mitigating motion blur challenges in tunnel inspection.

Frustrated total internal reflection (FTIR) is analyzed from a novel perspective. Unlike similar works, the angle of incidence is used here as the experimental variable instead of the film thickness through which light tunnels. This method makes it possible to visualize not only the phenomenon of FTIR but also the resonance processes that occur for angles of incidence below the critical angle. An affordable straightforward experiment appropriate for undergraduates is presented. The experiment involves measuring the reflection and transmission of light through a pair of prisms separated by an air or water layer, and the results are in fair agreement with theory.

ABSTRACTThe distance between adjacent tunnels is relatively small, and the driver passes through the alternating light environment for a short time, which poses great safety hazards to driving. Guided by the low‐carbon concept, it is of great significance to find an optimized light environment solution that integrates safety, low‐carbon, and economy. Based on the adjacent tunnel between Shuigou River and Songjiawa, this article evaluates and optimizes traditional lighting schemes and sunshade schemes from the above three aspects. The results show that the overall uniformity of road surface luminance for both schemes is greater than 0.313, which meets the regulatory requirements and is a feasible solution. Compared to traditional lighting schemes, the sunshade scheme reduces carbon emissions by 37.23% throughout its lifecycle, and reduces the present value of its lifecycle costs by 19.51%. From a comprehensive evaluation of the life cycle, the sunshade scheme is superior to the traditional lighting scheme.

PurposeGiven the expansion of cities and urbanization, developing efficient and reliable transportation infrastructure, especially urban tunnels, is essential. Failure to maintain such complex construction facilities with intelligent equipment systems could result in human losses and impose huge costs on governments. Therefore, it is necessary to have practical maintenance plans and operational safety monitoring for urban tunnels, which leads to their long lifespan, increases users’ safety and reduces operation risks.Design/methodology/approachHence, this research aims to evaluate the maintenance risks of urban tunnel lighting systems (UTLS) using a hybrid risk-based maintenance (RBM) approach. In this vein, three rounds of a fuzzy Delphi survey were conducted to consolidate the specific operation criteria and maintenance risk factors to the circumstances of Iran and UTLS. Furthermore, the fuzzy DEMATEL method was applied to determine the cause-and-effect relationships among the identified critical operation criteria. The identified risks associated with maintenance in UTLS were then analyzed and ranked using a combination of fuzzy ANP-VIKOR techniques.FindingsThe ranking of the various risks revealed that the “poor performance of switchboards in power supply due to faults in switchboard equipment” risk was ranked first, followed by the “poor performance of panels in the power supply due to unfavorable environmental conditions,” “The poor performance of panels in the power supply due to problems with switches (key failure)” and “The poor performance of panels in power supply due to burning fuses due to unauthorized current” risks. The findings of this study indicate that this hybrid maintenance method, developed as a risk-based network, provides reliability for maintaining urban tunnel lighting systems (UTLS).Originality/valueIt is anticipated that the findings of this research will considerably contribute to improving UTLS maintenance management while enhancing different stakeholders’ understanding of the most critical risks in maintenance, particularly toward the UTLS in Iran. An RBM management program can result in preparing and formulating policies, comprehensive guidelines or regulations for the maintenance of urban tunnels that are recommended for future research.