Artificial Intelligence-Assisted Control of Light Pipe & LED Luminaire Hybrid Tunnel Lighting System
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Abstract
Tunnels are designed as infrastructure elements that facilitate smoother traffic movement, enhance operational safety, and minimize environmental effects. However, when adequate lighting is not provided in tunnels, sudden transitions from bright outdoor environments to dim indoor spaces cause temporary vision loss while the eyes adapt to the new environment. Sudden changes in light at tunnel entrances and exits can disorient drivers and increase accident risks. Daylight offers a mix of wavelengths and color temperatures that provide optimal visual conditions for humans. In this study, an energy-efficient hybrid tunnel lighting system combining light tubes with artificial lighting was designed, and an artificial intelligence–based control system dependent on daylight was developed for this setup. To make tunnel conditions more efficient and comfortable for drivers, a control system incorporating an artificial neural network (ANN) algorithm was designed to apply the instantaneous outdoor illuminance level at the tunnel entrance. The control system results were analyzed, indicating that approximately 25.30% energy savings can be achieved compared to conventional lighting control methods, along with an expected improvement in drivers’ visual comfort.
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