城市区域交通状态判别方法研究

发布时间：2018-04-23 23:29

本文选题：交通状态判别 + 平均行程速度　；参考：《吉林大学》2014年硕士论文

【摘要】：目前，随着社会的进步经济的发展，车辆保有率的逐年增长，导致了交通需求快速增长。另一方面由于受到多方面的限制，交通供给却增长较为缓慢。供给与需求发展的不均衡造成了当下交通拥挤日趋常态化，而交通拥挤不仅导致了交通安全方面的诸多问题，更是增加了车辆的延误，尤其是城市道路中，对人们的出行带来了诸多不便。因此，有必要分析交通拥挤机理，明确交通拥挤度程度，以便为交通控制，交通诱导以及规划层面治理交通拥挤的手段方法提供前提条件以及可靠依据。本文在对比分析各交通状态指标的基础上，选取了能够科学反映区域宏观状态的指标。由于宏观指标一般不能够从检测器数据直接获得，因此本文建立了宏观指标与可获取的交通参数之间的关系。根据上述内容，本文具体研究如下：第一章为绪论，，主要阐述了区域路网交通流状态判别的研究背景，并分别从路段、交叉口层面和区域路网两个层面出发，对国内外相关研究现状展开分析和研究，针对目前研究中所存在的问题提出本论文研究的目的及意义，并进一步确定了论文的结构框架，为下文的展开奠定了基础。第二章为区域状态指标选取，在对前人相关研究分析的基础上，对其研究中所采用的交通状态指标分别从实时性、可获取性、准确性和直观性等方面进行了分析，并以此为参考基础选取区域状态评价指标。另外，对于检测技术手段，本文对比分析了各检测器的特点，在此基础上对本文所用检测数据类型做出了选择。第三章为区域行程速度估计，为了能够通过一些可测的交通参数间接计算得到可准确表征区域交通状态的区域状态指标，即区域平均行程速度，本章探究了排队长度与区域平均行程速度的关系，建立了二者相关性模型，从而架起了可测参数与区域交通状态指标之间的桥梁，并对其进行了仿真验证。第四章为排队长度计算模型，为了将由线圈检测器所采集到的地点交通流参数数据转化为排队长度参数，进而为行程速度估计模型提供必要的输入参量。本章根据元胞传输模型（CTM）估计得到每个元胞的交通流密度，描述了交叉口处的车辆排队演化过程，然后对队尾单元格的车辆到达与离去情况进行分析，对队尾确切位置进行了确定，在此基础上获得车辆的排队长度，并结合MATLAB编程语言和VISSIM交通流仿真软件进行了计算的简化和模型的验证。第五章为总结与展望，针对本文的相关研究成果、创新点和对下一步研究工作展望进行阐述。
[Abstract]:At present, with the development of society and economy, the vehicle retention rate increases year by year, which leads to the rapid growth of traffic demand. On the other hand, due to various constraints, traffic supply is growing slowly. The imbalance between supply and demand causes traffic congestion to become more and more regular, and traffic congestion not only leads to many problems in traffic safety, but also increases the delay of vehicles, especially in urban roads. It is inconvenient for people to travel. Therefore, it is necessary to analyze the mechanism of traffic congestion and make clear the degree of traffic congestion, so as to provide the precondition and reliable basis for the means of traffic control, traffic guidance and planning. On the basis of comparing and analyzing the traffic state indexes, this paper selects the indexes which can scientifically reflect the macroscopic state of the region. Because the macro index can not be obtained directly from the detector data, the relationship between the macro index and the available traffic parameters is established in this paper. According to the above contents, the specific research of this paper is as follows: The first chapter is the introduction, mainly elaborated the research background of the regional road network traffic flow state discrimination, and from the road section, the intersection level and the regional road network two levels, carries on the analysis and the research to the domestic and foreign related research present situation. The purpose and significance of this paper are put forward in view of the problems existing in the present research, and the structural framework of the thesis is further determined, which lays a foundation for the following work. The second chapter is the selection of regional state indicators. On the basis of previous research and analysis, the traffic state indicators used in the study are analyzed from the aspects of real-time, accessibility, accuracy and intuitiveness. On the basis of this reference, the evaluation index of regional state is selected. In addition, the characteristics of each detector are compared and analyzed, and the types of detection data used in this paper are selected. The third chapter is the estimation of regional travel speed. In order to get the regional state index which can accurately represent the regional traffic state by indirect calculation of some measurable traffic parameters, that is, the regional average travel speed, the regional average travel speed can be obtained. In this chapter, the relationship between queue length and regional average travel speed is explored, and the correlation model between them is set up, and the bridge between measurable parameters and regional traffic state index is set up and verified by simulation. The fourth chapter is the queue length calculation model, in order to convert the traffic flow parameters collected by the coil detector into queue length parameters, and then provide the necessary input parameters for the travel speed estimation model. In this chapter, the traffic density of each cell is estimated according to the Cellular Transport Model (CTM), and the evolution of the vehicle queue at the intersection is described, and then the arrival and departure of the vehicle in the trailing cell are analyzed. The exact position of the queue tail is determined and the queue length of the vehicle is obtained on the basis of which the calculation is simplified and the model is verified by combining the MATLAB programming language and the VISSIM traffic flow simulation software. The fifth chapter is the summary and prospect, aiming at the related research results, innovation points and the prospect of the next research.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491.1

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