Reliability Enhancement Driven by ANN for Lighting Control System in Highway Tunnels

Compared with open roadways, traffic safety in highway tunnels requires more attention to build smoothly transitioned and well-coupled light environments for drivers alleviate visual discomfort so as achieve a balanced sense of driving comfort. In this study, order overcome the drawbacks existing tunnel lighting control modes that disregard color temperature natural characteristics collaborative influence luminance on quality, one artificial neural network (ANN) model is designed trained simulate physical system takes into consideration simultaneously. model, multiple parameters discrete continuous types input layer output are synergistically analyzed. The was also quantities field data from service includes hidden 10 neurons. simulation results showed obtains high degree fitness inside 100% recognition rate threshold zone, which conforms regulation strategy actual systems confidence. proposed will greatly enhance reliability sustainability during its normal operation, can support other scenarios due flexibility scalability multiple-input multiple-output (MIMO) capabilities.