【摘要】 根据城市交通控制的非线性、随机性、模糊性和不确定性等特点,提出一种多路口信号优化控制方法。该方法通过神经网络技术对相关路口下一个周期的交通参数进行预测,并建立基于车辆排队的交通模型,同时,各路口的绿信比在周期内也可根据当前的交通状况实时调整,以克服预测模型失配和外界干扰的影响,最终达到了多路口交通畅通和平均车辆延误时间尽可能小的控制目标。仿真试验已证实了该方法的有效性。更多还原

【Abstract】 According to the features of metropolitan traffic control,i.e.non-linear,random,fuzzy and undeterministic,etc.,the optimization method for controlling traffic signals of multiple crossroads is proposed.By this method,the traffic parameters of the next cycle for related crossroads are predicted through neural network technology,and the traffic model is established based on the vehicles’ queue.Also,the duty ratio of the green light at each crossroad can be adjusted real time in accordance with the traffic situation,thus the influence of mismatch of predicted model and external interference can be overcome.The control goal of unblocked traffic and minimized average waiting time is accomplished.The simulation test has shown the effectiveness of this method.更多还原