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城市道路车道缩减区驾驶行为特征及交通仿真研究

发布时间:2018-03-29 08:36

  本文选题:车道缩减区 切入点:元胞自动机 出处:《长沙理工大学》2014年硕士论文


【摘要】:城市道路车道缩减区常见于道路与桥梁过渡段、地铁施工区等。近年来,城市轨道交通兴起,其施工建设导致车道缩减区尤为普遍。在缩减区,由于部分车道中断、车道数突变,道路局部路段通行能力骤降,成为了城市交通拥堵的频发区域。如何深入解析车道缩减区驾驶行为特征,准确评估车道缩减区对车辆行驶以及道路交通的影响,对于指导车道缩减区交通设计和组织管理,缓解城市路网交通瓶颈问题具有重要意义。元胞自动机是一种时间、空间和变量均离散的数学模型,在交通流模型与仿真应用研究中受到广泛关注。本文在总结元胞自动机交通流模型研究现状特征的基础上,结合车道缩减区驾驶行为和交通运行特征数据采集,构建了车道缩减区的元胞自动机模型,利用MATLAB编写了仿真程序,利用新的仿真程序对3类车道缩减区进行仿真模拟,分析、得到了各类车道缩减区的交通流运行特性以及驾驶行为特征。具体内容包括:分析国内外关于车辆驾驶行为及交通仿真的研究现状,总结现有交通仿真中的跟车与换道模型以及元胞自动机模型的特性。以长沙市多个典型车道缩减区为对象开展调查,得到了不同车道缩减区的运行特征参数,包括:车头间距、车速、最大车速、高峰小时流量以及缩减区内车辆换道比例等驾驶行为特征值。构建了车道缩减区元胞自动机模型,从一维多车道元胞自动机交通流模型入手,引入车道缩减影响的元胞自动机模型,并结合调查数据对元胞自动机模型进行.参数标定。采用MATLAB开发了车道缩减区的交通仿真程序,利用仿真程序对3类车道缩减区进行仿真实验,分别得到车道缩减区的交通运行特征结果,包括:流量、密度、速度等。基于仿真结果,采集不同交通条件下(密度变化)车道缩减区内车辆换道、跟驰行为,得到换道比例特征,进而得到车道缩减区对车辆行驶以及道路交通影响的密度区间。
[Abstract]:Urban road lane reduction areas are common in the transitional sections of roads and bridges, subway construction areas, etc. In recent years, urban rail transit has emerged, and the construction of urban rail transit has led to a particularly common lane reduction area. In the reduced area, due to the interruption of part of the carriageway, The sudden change in the number of lanes and the sudden decline in the capacity of some sections of the road have become the frequent areas of urban traffic jams. How to analyze the driving behavior characteristics of the reduced lane areas and accurately evaluate the impact of the lane reduction areas on vehicle driving and road traffic, Cellular automata is a mathematical model with discrete time, space and variables, which is of great significance to guide traffic design, organization and management of lane reduction area and alleviate the traffic bottleneck problem of urban road network. On the basis of summarizing the current research features of cellular automata traffic flow model and combining with the data collection of driving-behavior and traffic characteristics in the driveway reduction area, this paper focuses on the research of traffic flow model and simulation. The cellular automata model of lane reduction area is constructed, and the simulation program is written by MATLAB, and three kinds of lane reduction areas are simulated and analyzed by using new simulation program. The characteristics of traffic flow and driving behavior in various driveway reduction areas are obtained. The specific contents are as follows: the current situation of research on vehicle driving behavior and traffic simulation at home and abroad is analyzed. This paper summarizes the characteristics of the following and changing models and cellular automata models in traffic simulation. Taking several typical lane reduction areas in Changsha as the research object, the operation characteristics of different lane reduction areas are obtained, including: headway spacing. The characteristic values of driving behavior, such as speed, maximum speed, peak hour flow and the proportion of vehicles changing lanes in the area are reduced. The cellular automata model of driveway reduction area is constructed, which starts with the traffic flow model of one-dimensional multi-lane cellular automata. The cellular automata model with lane reduction effect is introduced, and the cellular automata model is calibrated with investigation data. The traffic simulation program of lane reduction area is developed by MATLAB. The simulation results of three types of lane reduction areas are obtained by using the simulation program, including the traffic flow, density, speed, etc. Based on the simulation results, the traffic characteristics of the three types of lane reduction areas are obtained, including the traffic flow, the density, the speed, and so on. Through collecting the changing and car-following behavior of vehicles in different traffic conditions, the proportional characteristics of lane change are obtained, and then the density interval of the effect of lane reduction area on vehicle driving and road traffic is obtained.
【学位授予单位】:长沙理工大学
【学位级别】:硕士
【学位授予年份】:2014
【分类号】:U491


本文编号:1680361

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