Tunnels, as critical components of road transportation infrastructure, pose major challenges in terms of lighting energy consumption and carbon emissions and their light environment quality has a significant impact on driving safety. Addressing these challenges is essential to ensure operational safety and achieve carbon reduction targets. Based on drivers′ visual information perception characteristics, tunnel lighting energy-saving technologies are classified into three categories: mitigation of light-dark adaptation at portals, optimization of the internal light environment, and control of lighting. The authors systematically review the energy-saving principles, implementation effectiveness, and existing limitations of these technologies. Furthermore, an energy-saving and lowcarbon lighting framework based on the equivalent integration of the driver-vehicle-tunnel light environment system is proposed. The main conclusions are as follows. (1) Current tunnel lighting technologies inadequately consider the dynamic interaction mechanisms among the driver, vehicle, and tunnel lighting environment; exhibit suboptimal energy efficiency throughout their life cycles; and lack systematic integration and digitalization. (2) Three levels of "equivalence" in tunnel lighting are proposed: equivalence of physical quantities related to drivers′ visual information perception characteristics, equivalence of biological quantities, and the synergistic equivalence of physical and biological quantities, with corresponding definitions and evaluation criteria discussed. (3) Based on these equivalence concepts, implementation pathways for digital low-carbon tunnel lighting technology are outlined, including the development of safety and carbon-emission-oriented equipment for the full operational life cycle, tunnel-specific evaluation methods for operational energy efficiency and carbon emissions, and a comprehensive digital twin framework integrating the driver-vehicle-tunnel lighting environment system.
HE Shiyong
,
ZHAO Junhao
,
LIANG Bo
,
XU Da
,
QIN Li
,
XIAO Yao
,
NIU Jia′an
,
LIU Hao
. Research Progress on Energy-Saving and Low-Carbon Tunnel Lighting Technologies Based on Drivers′ Visual Information Perception Mechanisms[J]. Tunnel Construction, 2025
, 45(10)
: 1803
-1815
.
DOI: 10.3973/j.issn.2096-4498.2025.10.001