Energy-saving Algorithm for Highway Tunnel Lighting Based on Self-supervised Learning
A deep learning based optimization algorithm for highway tunnel lighting matrix is proposed to address the issues of high power consumption,high cost,and the impact of lighting on driving safety in highway tunnels. The algorithm effectively utilizes the existing equipment in the highway tunnel,combines the backbone models of ResNet and YOLO,and imposes a soft constraint on the loss function end on the basis of integrating the driving safety signs and self-supervised learning technology. While ensuring driving safety and reducing lighting energy consumption,it automatically outputs a tunnel lighting parameter matrix and dynamically adjusts the lighting equipment in the tunnel using this matrix. The experiment shows that the proposed algorithm reduces the energy consumption of tunnel lighting while ensuring that the tunnel lighting can guarantee driving safety.
highway tunnelsafe and energy-savingdeep learningmachine vision
万方数据
维普
