基于车路协同的区域交通信号控制技术研究

发布时间：2018-03-28 17:19

本文选题：车路协同　切入点：区域控制　出处：《北方工业大学》2017年硕士论文

【摘要】：随着城市规模的不断扩大,交通拥堵已经成为大城市中普遍存在的问题,并且由此带来了一系列的社会问题。为了解决日益严峻的交通拥堵问题,各国相继提出了智能交通系统的概念。车路协同技术作为智能交通系统的前沿技术,是解决城市道路拥堵的有效方法之一,得到了各国交通工作者的重点关注。车路协同系统基于无线通信和传感器检测等技术获取车辆和道路的有效信息,通过建立车车通信、车路通信,将人、车、路三者有效的联系起来,完成车辆和路旁基础设施之间的交互,充分利用基础设施和道路资源,提高道路的利用率,改善交通的安全,缓解交通拥堵现象。本文主要研究了智能交通系统中的区域交通控制,重点研究了车路协同环境下的区域交通信号控制。主要完成了以下几个方面的工作:(1)首先,总结了区域交通信号控制的发展状态,着重研究了区域子区划分的方法,提出了车路协同环境下基于状态分析的控制小区划分算法,以路网的行程时间为主要因素,结合交叉口之间的连通性,通过设定拥堵程度阈值,确定关键路口,并以此为核心进行子区划分。(2)对车路协同环境下的区域控制进行了相关研究,提出了基于K均值聚类的区域交通信号控制策略,通过车路协同环境下的检测技术获取车辆的精确信息,计算出各个车辆到达路口所需的时间,利用K均值聚类分成两大类,并以此来调整绿灯时间,同时检测等待时间最长的相位作为下一个通行相位。(3)搭建了车路协同环境下的优先信号控制平台,利用手机等移动设备作为用户端,同时利用百度地图获取车辆的位置,实时监测车辆行驶方向和速度,通过调整最近邻的交通信号,从而实现部分车辆的优先运行,并在北京市长安街进行了实际项目验证。
[Abstract]:With the continuous expansion of urban scale, traffic congestion has become a common problem in large cities, and has brought a series of social problems. The concept of intelligent transportation system has been put forward one after another. As the frontier technology of intelligent transportation system, vehicle-road coordination technology is one of the effective methods to solve urban road congestion. Based on wireless communication and sensor detection and other technologies to obtain effective information of vehicles and roads, through the establishment of vehicle-vehicle communications, vehicle-road communications, people, cars, The three roads are effectively linked to complete the interaction between vehicles and roadside infrastructure, make full use of infrastructure and road resources, improve road utilization, and improve traffic safety. In this paper, we mainly study the regional traffic control in intelligent transportation system, and focus on the regional traffic signal control under the environment of vehicle-road coordination. In this paper, the development of regional traffic signal control is summarized, the method of regional sub-area division is studied emphatically, and the algorithm of control cell partition based on state analysis is put forward in the collaborative environment of vehicle and road, with the travel time of road network as the main factor. According to the connectivity between intersections, the key intersection is determined by setting the threshold of traffic congestion, and the sub-area is divided as the core. (2) the regional control under the collaborative environment of vehicle and road is studied. A traffic signal control strategy based on K-means clustering is proposed in this paper. The accurate information of vehicles is obtained by the detection technology in the vehicle-road cooperative environment, and the time required for each vehicle to reach the intersection is calculated, and the K-means clustering is divided into two categories. In this way, the green time is adjusted, and the phase of the longest waiting time is detected as the next phase.) the priority signal control platform under the collaborative environment of vehicle and road is built, and mobile devices such as mobile phone are used as the client. At the same time, Baidu map is used to obtain the position of the vehicle, to monitor the direction and speed of the vehicle in real time, to realize the priority operation of some vehicles by adjusting the traffic signal of the nearest neighbor, and to carry out the actual project verification in Changan Street, Beijing.
【学位授予单位】：北方工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491.54;TP273

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