Research on Dynamic Optimization and Control Mechanism of Intelligent Photoelectric Lighting in Expressway Tunnel

Abstract

To address driving safety risks and energy waste caused by significant brightness fluctuations on road surfaces, this study proposes a dynamic optimization and intelligent control method for highway tunnel lighting environments. Through field experiments and data analysis under various spatiotemporal conditions, we identified consistent visibility patterns within tunnels. The dynamic optimization framework incorporates visibility, traffic flow, vehicle speed, measured pavement luminance, and lighting luminance. Based on this framework, an FRBF controller is developed using visibility, traffic flow, and vehicle speed as input variables to generate the required lighting-control signal. Using actual measurement data from highway tunnels across multiple regions, together with typical lighting scenarios, an FRBF-based intelligent control model for highway tunnel lighting is established. Simulation experiments validate the effectiveness of the proposed method, showing that it can maintain pavement luminance close to the design requirements while improving lighting energy efficiency.