摘要
为实现隧道内"灯光随车移动"控制技术,在隧道合适位置布设测速线圈,采用RBF神经网络模型预测相邻线圈间的车速。根据隧道特点建立隧道停车视距模型,从而确定了既符合实际又能保证行车安全的灯光长度。最后,给出照明灯智能控制思想。实例分析表明,当交通量低于3 000辆/天时,节能率能达到90%以上。
We deployed velocity coils at some suitable locations and employed RBF neural network to predict the velocity between two adjacent coils for the implementation of such intelligent control technology as light following vehicle.We also constructed a tunnel characteristic based tunnel stopping sight distance model,which determined a realistic and safe light length.We eventually presented the idea of smart illumination control.The analysis of practical cases shows that energy saving rate is more than 90% when the traffic throughput is lower than 3 000 pcu a day.
出处
《山东科学》
CAS
2012年第4期64-68,共5页
Shandong Science
基金
国家重点基础研究发展计划(973计划)(2012CB725403)
中央高校基本科研业务费专项资金(T11JB00330)
关键词
隧道照明
RBF神经网络模型
隧道停车视距
智能控制
tunnel illumination
RBF neural network model
tunnel stopping sight distance
intelligent control
