基于路口相位方案优化设计的城市道路交通信号迭代学习控制方法研究

城市道路交叉口信号控制是交管工作持续关注的课题,关于协调好有限的道路资源与日益增长的交通需求之间的矛盾,有着至关重要的作用。由于道路自身条件约束,交通流的组成特点复杂,路网交通路呈现非线性动态特征,无法进行精准的数学建模控制。本文提出的迭代学习控制方法,根据交通流的组成和变化特点调整信号控制周期及有效绿灯时长,实现交通信号动态优化控制,保证车辆在路网中能够高效、平稳地通行,是针对非线性动态交通流的一种动态寻优控制算法,能够有效减少路口车辆等待时间、提高通行效率。考虑对不同相位设计方案的适应性,在传统配时优化模型的基础上,构建综合相位设计元素的交通信号迭代学习控制模型,并通过Vissim仿真软件和Python编程语言搭建仿真测试环境,验证了提出模型的有效性。

Iterative Learning Control of Traffic Signals Considering Phase Scheme Design

The signal control of Urban Road intersection is the topic of traffic management work.It plays an important role in coordinating the contradiction between the limited road resources and the growing traffic demand.Due to the constraints of road conditions,the composition of traffic flow is complex,and the traffic road network presents nonlinear dynamic characteristics,so it is impossible to carry out accurate mathematical modeling control.The iterative learning control method proposed in this paper adjusts the signal control cycle and effective green time according to the composition and variation characteristics of traffic flow,realizes the dynamic optimization control of traffic signal,and ensures that vehicles can pass efficiently and smoothly in the road network.It is a dynamic optimization control algorithm for nonlinear dynamic traffic flow,which can effectively reduce the waiting time of vehicles at intersections and improve the traffic efficiency.Considering the adaptability to different phase design schemes,based on the traditional timing optimization model,the traffic signal iterative learning control model with phase design elements is constructed.The simulation environment is built by VISSIM and Python to verify the effectiveness of the proposed model.