Conventional tunnel lighting systems face challenges
such as high energy consumption and limitations in dynamically coordinating
real-time traffic flow with luminance parameters inside/outside tunnels
for energy-saving control. To address these challenges,
the authors propose a real-time tunnel lighting
regulation system based on multi-source data fusion.
First, a heterogeneous data fusion architecture combining millimeter-wave radar and luminance detectors is designed, achieving
millisecond-level synchronous perception of traffic
volume, vehicle speed, and intra/extra-tunnel
luminance. Subsequently, an edge-cloud collaborative
dimming model is constructed, where edge computing nodes execute lightweight
algorithms to generate real-time dimming commands,
while cloud-based optimization of threshold parameters
is performed through long-term data training. Finally,
a regional "on-demand real-time dimming" strategy is proposed to adaptively match baseline
illumination with exterior luminance. A management platform integrating multi-source data analysis, three-dimensional
visualization, and lighting status monitoring ensures real-time tunnel safety. Experimental deployment in the left tunnel of a
Yunnan province case study demonstrates that the system achieves energy-saving ratios of 63.90%－67.43% compared to
time-sequence circuit control under high traffic
volumes (>1 500 vehicles per day). During low-traffic
periods (≤1 500 vehicles per day), energy-saving efficiency exhibits a negative correlation with traffic
volume, reaching up to 88.43%, while fully complying with tunnel operational
safety standards.
ZHANG Kaiwen
,
HE Yongjun
,
ZHANG Yun
,
WANG Jin
,
SHUAI Chunyan
. Application of Real-Time Regulation Energy-Efficient System for Highway Tunnel
Lighting[J]. Tunnel Construction, 2025
, 45(S1)
: 71
-79
.
DOI: 10.3973/j.issn.2096-4498.2025.S1.008
