车联网环境下交叉口群速度引导模型及仿真

发布时间：2019-05-23 21:49

【摘要】：机动车保有量激增,导致城市交通拥堵问题日益严重,交通安全与环境污染问题日益突出。作为城市路网交通流主要集散点,交叉口的信号控制策略、车辆排队是造成交通拥堵的关键原因之一。以交叉口群作为管控对象用于缓解城市交通拥堵问题已经成为研究共识,随着车联网技术的快速发展,基于该技术实现交叉口群车辆的速度引导,将为缓解城市交通拥堵问题提供一种有效的解决策略。本文针对城市主干道路线性交叉口群设计了速度引导算法,形成“动态绿波带”实现车联网环境下的交叉口群车速引导,缓解城市交通拥堵。首先,从动态速度控制、动态速度引导、车联网环境特征测试、交叉口群速度引导和技术应用等方面,对国内外的速度引导研究现状进行了总结,给出了本文的研究内容和技术路线。在介绍车联网的系统构建、技术体系和作用机理基础上,对比分析了传统行驶环境与车联网行驶环境下速度引导方法的差异,并对车联网环境下速度引导机理与基本方法进行了论述。然后,介绍了交叉口群的基本概念、特性和界定方法,基于上述两种环境下速度引导差异性分析,分别提出了基于单点、协同两种场景的线性交叉口群速度引导算法,包括引导策略、算法设计与流程等。为验证算法有效性,考虑车联网速度引导影响因子,基于EstiNet仿真软件构建了两种场景下速度引导算法测试环境。针对EstiNet软件提供的车载、信号、路侧等三种智能体二次编程开发,实现了论文提出的交叉口群单点、协同速度引导算法。最后,利用设计的车联网环境速度引导评价指标体系,从运行效率、污染排放和行驶安全等方面对速度引导算法的效果进行了定量分析,对比分析两种速度引导算法的效果,并结合车联网环境速度引导影响因子对算法敏感性进行研究。同时,利用行车速度、车头时距分析了车联网环境下的交通流特征。仿真结果显示,实施交叉口群协同速度引导策略后,平均速度、行程时间可靠性分别改善了 13.36%、76.61%,停车时间、延误时间、可达性阻隔系数、污染排放和速度连续性分别下降了 51.02%、65.79%、86.32%、7.07%、23.89%。相对于交叉口群单点速度引导,协同速度引导减少了 19.64%的不必要速度引导信息推送,对评价指标也具有更好的改善效果。对影响因子敏感性分析表明,设备装载率和引导遵从率的上升以及通信距离的降低,会使得评价指标的改善程度更为明显。此外,交通流特征分析方面,两种环境下车辆的行车速度和车头时距都可以分别采用正态分布和移位负指数分布进行拟合,且引导车辆通过交叉口停车线处的行车速度提升了 51.81%,车头时距减小了 24.67%,表明提出的算法提高了通行效率,缓解了城市交叉口群的拥堵。
[Abstract]:The proliferation of motor vehicle ownership leads to the increasingly serious problem of urban traffic congestion, and the problems of traffic safety and environmental pollution are becoming more and more prominent. As the main distribution point of traffic flow in urban road network, the signal control strategy of intersection, vehicle queuing is one of the key reasons for traffic congestion. It has become a research consensus that cross-port group is used as the control object to alleviate the problem of urban traffic jams. With the rapid development of vehicle networking technology, the speed guidance of cross-port group vehicles is realized based on this technology. It will provide an effective solution to alleviate the problem of urban traffic congestion. In this paper, a speed guidance algorithm is designed for the linear crossing group of urban main roads, and a "dynamic green wave belt" is formed to guide the speed of the intersection group in the environment of vehicle networking, so as to alleviate the traffic congestion in the city. First of all, from the aspects of dynamic speed control, dynamic speed guidance, vehicle network environmental characteristics test, intersection group speed guidance and technical application, the research status of speed guidance at home and abroad is summarized. The research content and technical route of this paper are given. On the basis of introducing the system construction, technical system and action mechanism of vehicle networking, this paper compares and analyzes the differences of speed guidance methods between traditional driving environment and vehicle networking driving environment. The mechanism and basic method of speed guidance in vehicle networking environment are discussed. Then, the basic concept, characteristics and definition method of the intersection group are introduced. based on the analysis of the difference of velocity guidance in the above two environments, the speed guidance algorithm of linear intersection group based on single point and cooperative scene is proposed respectively. Including guidance strategy, algorithm design and process, and so on. In order to verify the effectiveness of the algorithm, considering the influence factors of vehicle network speed guidance, the test environment of speed guidance algorithm in two scenarios is constructed based on EstiNet simulation software. Aiming at the secondary programming of vehicle, signal and road side provided by EstiNet software, the single point and cooperative speed guidance algorithm of intersection group proposed in this paper is realized. Finally, the effect of the speed guidance algorithm is quantitatively analyzed from the aspects of running efficiency, pollution discharge and driving safety, and the effects of the two speed guidance algorithms are compared and analyzed by using the designed speed guidance evaluation index system of the vehicle network environment. The sensitivity of the algorithm is studied by combining the influencing factors of speed guidance in vehicle networking environment. At the same time, the traffic flow characteristics in the vehicle network environment are analyzed by using the driving speed and the front time distance. The simulation results show that the average speed and travel time reliability are improved by 13.36%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61%, 76.61% and 76.61%, respectively. Pollution emissions and speed continuity decreased by 51.02%, 65.79%, 86.32%, 7.07% and 23.89%, respectively. Compared with the single point speed guidance of intersection group, the cooperative speed guidance reduces the unnecessary speed guide information push by 19.64%, and also has a better effect on the evaluation index. The sensitivity analysis of the influencing factors shows that the increase of equipment loading rate and guide compliance rate and the decrease of communication distance will make the improvement of evaluation index more obvious. In addition, in the analysis of traffic flow characteristics, the driving speed and headway time distance of vehicles in the two environments can be fitted by normal distribution and displacement negative exponential distribution, respectively. The driving speed of the guided vehicle through the intersection parking line is increased by 51.81%, and the headway time distance is reduced by 24.67%, which indicates that the proposed algorithm improves the traffic efficiency and alleviates the congestion of the urban intersection group.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U495

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