Intelligent control and energy saving evaluation of highway tunnel lighting: Based on three-dimensional simulation and long short-term memory optimization algorithm

The influence of dimming-induced luminance change on driving safety in tunnels

“…The corresponding luminance change during this time of dimming was thus L 2 th1− L 1 th1 which depended on the change in L 20 between two times of dimming, i.e., L 2 20− L 1 20. In practical situations, the time interval between two times of dimming is usually 10 min [ 7 ]. During this interval, the maximum change amplitude of L 20 reaches 2 kcd/m 2 according to the above L 20 measurements.…”

“…According to the International Commission on Illumination (CIE), L th should be designed based on three references, i.e., the highest L 20 (likely to occur during at least 75 daytime hours per year), the maximum traffic flow, and the maximum vehicle speed [ 4 ]. However, the actual L 20 , traffic flow, and vehicle speed, are often much smaller than the above references [ 5 , 6 , 7 , 8 ]. Therefore, if the threshold zone luminance always adopts the designed value, it will lead to the fact that the lighting luminance is much higher than the real demand during the 95% of the daytime [ 9 ], thus resulting in over-illumination [ 10 ].…”

“…This system can save 30% energy consumption. The lighting demand calculation model was further improved by Zhao [ 7 ] using the LSTM algorithm, which achieved continuous dimming and increased energy savings of the dimming system to around 40%. In addition, based on data retrieved from 11 tunnels, Qin [ 17 ] explored the influences of tunnel length, traffic flow, and service time on initial investment and electrical costs for four kinds of dimming systems.…”

Intelligent dimming control and energy consumption monitoring system of tunnel lighting

“…The fourth category is the use of intelligent control methods [21][22][23][24][25][26] to regulate the luminance of luminaires in tunnel lighting systems. Such methods are the most common and effective way of reducing energy consumption through internal optimization of the system.…”

Fuzzy Control Strategy of Tunnel Lighting Based on Input Parameter Optimization

“…Qin et al [4] used PID closed-loop feedback adjustment to keep the required brightness and the interior tunnel road surface brightness consistent to ensure the tunnel lighting demand. Zhou et al [5] and Zhao et al [6] fitted the relationship between the detected luminance outside the cave, traffic volume, and speed as a function of the demanded brightness in each tunnel section through neural networks, respectively.…”