城市交通流协调模糊控制模型

A model of coordinate fuzzy control for urban traffic flow control

针对交通路口拥堵问题,提出基于神经网络与协调模糊控制相结合的数学模型。该模型首先通过BP神经网络输出各种路况信息,然后将这些信息以模糊隶属函数表示,进而通过模糊推理控制规则推导出控制策略。与已有模型相比,该模型采用OBD设备,能够实时捕捉车辆信息,而且考虑较多的路况信息,更符合实际情况。仿真结果表明,该模型能通过动态分配信号灯时间,有效降低交通路口拥堵风险。

A mathematical model,which is based on neutral network and coordinate fuzzy control,is proposed to solve traffic congestion. This model first uses BP neutral network to output traffic conditions,and then expresses these by fuzzy membership functions,and finally reasons about control policies by fuzzy control rules. Compared with the existing model,this model uses OBD equipment to collect real-time data. Moreover,it considers more traffic conditions and accords with practical situation. Simulation results show that the model works well in reducing traffic intersection congestion risk by allocating time dynamically.