车路协作式交叉口车速引导技术研究

发布时间：2018-01-07 17:10

本文关键词：车路协作式交叉口车速引导技术研究　出处：《北方工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着社会的发展,机动车保有量和道路交通量急剧增加,仅靠传统的交通管理及技术已无法解决交通拥堵、交通安全等问题。而车路协同技术是智能交通的重要组成部分,该技术的运用将有助于提高城市道路交通安全,缓解拥堵,降低尾气排放,进而能够有效提高道路交通整体效益;智能网联车辆是指搭载先进的车载传感器、控制器和执行器等装置,并融合现代通信与网络技术,使车辆具备复杂环境感知、智能化决策与控制等功能,同时可以实现安全、节能、环保及舒适行驶的新一代智能车辆。结合智能网联车辆和车路协同的特点,本文在车路协同环境下首先对单车进行车速引导研究,进一步结合多智能体理论对车辆编队进行研究。研究工作总结如下:第一,交叉口车辆速度引导研究。本文首先对车路协同系统场景进行设计,然后结合车辆运动规律及交叉口信号控制等因素,建立交叉口速度引导模型,进一步考虑车辆在行驶过程中能与前车进行信息交互,通过运动学规律计算车辆行驶中的实时安全距离,并以车均延误最小为目标,建立了速度引导模型。对车辆速度引导模型进行仿真验证,并分析仿真结果。第二,车辆编队控制算法研究。传统车辆编队是通过车辆间的跟驰行为形成队列的,形成的队列不稳定且不受控。因此本文首先对车辆编队进行图论描述,然后运用位移和速度等参数建立二阶多智能体方程以加速度作为系统控制输入,并对控制输入进行设计,进而建立了适合城市道路车辆编队的控制模型,并进行仿真验证。第三,车辆编队与交叉口信号控制结合。在以上研究的基础上,将车辆编队运用在交叉口,结合交叉口信号控制建立智能网联车辆编队控制模型。该模型首先对交叉口信号状态进行划分,然后对于进入编队区域的车辆的队列规模进行划分,同时对进入编队区域的车辆进行编队,最后队列通过速度引导不停车通过交叉口。通过Vissim/Vb/Matlab联合仿真验证模型的有效性。
[Abstract]:With the development of society, the amount of vehicle and traffic volume increase sharply, and the traditional traffic management technology has been unable to solve the traffic congestion, traffic safety and other issues. And the vehicle road coordination technology is an important part of the intelligent transportation system, the use of the technology will help improve the city road traffic safety, alleviate congestion, reduce exhaust emissions, and can effectively improve the overall efficiency of the road traffic network; intelligent vehicle is equipped with advanced vehicle sensor, controller and actuator device, and the integration of modern communication and network technology, the vehicle with complex environment perception, intelligent decision-making and control functions, and can realize the safety, energy saving, environmental protection and comfort driving a new generation of intelligent vehicle. According to the characteristics of intelligent vehicles and road network collaborative environment, first bicycle car speed on the road vehicle guidance research collaboration, in One step based on multi-agent theory to study vehicle formation. Research work is summarized as follows: first, study guide intersection vehicle speed. This paper carries on the design to the CViS scene, and then combined with the vehicle motion and the intersection signal control and other factors, the establishment of the intersection speed guidance model, vehicle information can be further considered the interaction with the front of the car in the running process, real-time calculation of safety distance of vehicles through the kinematics rule, and the average vehicle delay minimum as the goal, set up speed guidance model. The vehicle speed guide model simulation and analysis of simulation results. Second algorithms, the study on formation control of vehicles. The traditional vehicle formation by vehicle the following behavior form a queue, queue formed are not stable and controlled. Therefore this paper first graph description of the vehicle fleet, and then use a Displacement and velocity parameters to establish two order multi-agent system equation for the acceleration as control inputs, and the control input is designed, and then established the control model for city road vehicle fleet, and simulation. Third, vehicle formation combined with intersection signal control. On the basis of the above research, the vehicle fleet in the intersection, the establishment of intelligent control network of vehicle formation control model with the intersection signal. The model first to classify the intersection signal, and then to scale into the region of the vehicle queue formation in the division, at the same time to enter the area of the vehicle fleet formation, finally through the queue speed guidance through the intersection without stopping. The effectiveness of the joint simulation of Vissim/Vb/Matlab model.

【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

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