Traffic Safety Improvement via Optimizing Light Environment in Highway Tunnels

Abstract

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.

Reliability Enhancement Driven by ANN for Lighting Control System in Highway Tunnels

“…(3). It should provide reasonable light environment indexes that help to improve the driving safety and comfort requirements in the tunnel area [13], which are also covered in the specifications in (1), for instance:…”

“…In this study, the reliability model discussed stems from one tunnel lighting system with the same framework as [13], the reliability block diagram (RBD) in Figure 8 can be used to analyze its system reliability.…”

“…After this, the lighting neural network training is completed, and the dimming results of the actual system should be used to verify whether overfitting happens with the training model. Songshan tunnel lighting system [13] has accumulated quantities of field data since its online operation. In this simulation, data labels are constructed based on the light sensing data and control records of target luminance and color temperature in the threshold zone for 12 h continuously from 6:00 to 18:00 in normal weather, with a sampling period of 10 min, and then these labels are used to verify the validity of this lighting neural network.…”

When Lights Can Breathe: Investigating the Influences of Breathing Lights on Users’ Emotion

“…The influences of light intensity, spectrum, and colour temperature have been extensively investigated in the current literature [ 1 , 2 , 3 , 4 , 5 ]. The research findings have been widely applied in a variety of fields, including medicine, transportation, and marketing communication [ 6 , 7 , 8 ]. Hartstein et al found that adolescents exposed to low correlated colour temperature (CCT) had better sleep quality and were less exhausted the next day [ 9 ].…”

“…A study by van Bommel and van den Beld showed that switching from 300 lux to 500 lux illumination increased productivity in the metal-working industry by approximately 8%, whereas switching from 300 to 2000 lux generated a 20% improvement in productivity [ 10 ]. Dynamic light environments, which change in response to the natural environment and the physiological state of the human body, are a hot topic of research and have been shown to improve road safety [ 7 ].…”