摘要
传统的智能配时方法在解决城市复杂轨道交通信号配时问题时,存在时间延误、实际应用能力差的问题。为了解决上述问题,以仿真方法研究了一种新的城市复杂轨道交通信号智能配时方法。在Hopfield模型的基础上建立双层反馈网络,通过双层反馈网络计算出车辆延误值、饱和流量值,进而开发出能量函数,根据开发的能量函数对双层反馈网络进行智能优化,优化过程包括交通数据采集、饱和度计算、优化计算、结果处理、结果发送五步。通过仿真实验验证了设计的智能配时方法的性能,结果表明,给出的配时方法可以很好地解决时间延误的问题,并且可以针对具体情况进行调试。
Time delay occurs when the traditional intelligent time distribution method is used for the time distribution of urban complex rail transit signals.Therefore,the performance of practical application is poor.In view of the above,a new intelligent time distribution method for urban complex rail transit signals is studied by simulation method.A double⁃layer feedback network is established on the basis of Hopfield model.The vehicle delay value and saturated flow value are calculated by the double⁃layer feedback network,so as to develop the energy function.According to the developed energy function,the double⁃layer feedback network is intelligently optimized.The optimization process includes five steps,named traffic data collection,saturation calculation,optimization calculation,result processing and result sending.The performance of the designed intelligent time distribution method is verified by simulation experiments.The results show that the proposed time distribution method can avoid the time delay and can be used for debugging as specific conditions.
作者
庞彦知
PANG Yanzhi(Nanning University,Nanning 530200,China)
出处
《现代电子技术》
北大核心
2020年第21期80-84,共5页
Modern Electronics Technique
基金
2017年度南宁市人才小高地专项资金资助项目:高铁列控中心系统失效机理研究(2017042)
南宁市科学技术局科技基地专项项目:高速铁路信号系统安全测试研究与应用(20185211)
2018年南宁市青年科技创新创业人才培育项目:南宁地铁4号线列车自动驾驶停车精度及节能优化研究(RC20180109)。
关键词
人工智能
城市复杂轨道
交通信号
智能配时
HOPFIELD模型
双层反馈网络
artificial intelligence
urban complex track
traffic signal
intelligent time distribution
Hopfield model
double⁃layer feedback network
