针对目前隧道照明中存在的能源浪费问题，提出一种基于模糊神经网络算法的隧道照明控制策略，进一步降低隧道照明控制系统的能耗。具体是将实时采集的隧道口洞外亮度、过往的车流量及车速作为照明控制系统的输入量，隧道各照明段的回路调光值作为照明控制系统的输出量，搭建1个3输入-单输出的控制模型，重点对模型的建立和算法的机理及训练进行分析。最后通过仿真实验验证该算法在隧道照明中的节能效果，为现阶段隧道照明控制的相关研究提供一定的参考。

The energy waste problem of illumination system in tunnel is serious. In order to reduce the energy consumption of tunnel illumination control system, a kind of tunnel illumination control strategy based on fuzzy neural network algorithm is put forward. The realtime collection of brightness outside the tunnel portal, the traffic flow and the vehicle speed are taken as input values of the illumination control system; the illumination loop dimming values collected from every illumination tunnel section are taken as the output values of the illumination control system; a illumination control model with tripleinput and singleoutput is established; and the mechanism and training of the establishment and caululation of the model are analyzed. The energysaving effect of the model for tunnel illumination control system is verified by experimental simulation, which can provide reference for present study of tunnel illumination control.