交通运输系统工程与信息

交通运输系统工程与信息 ›› 2017, Vol. 17 ›› Issue (3): 105-111.

• 智能交通系统与信息技术 • 上一篇    下一篇

一种考虑交叉口因素的改进元胞传输模型

姚凯斌，林培群*   

  1. 华南理工大学土木与交通学院，广州510640
  • 收稿日期:2016-08-18 修回日期:2017-02-09 出版日期:2017-06-25 发布日期:2017-06-26
  • 作者简介:姚凯斌（1993-），男，广东揭阳人，硕士生.
  • 基金资助:

    国家自然科学基金项目/National Natural Science Foundation of China（61573149，61572233）；广东省交通厅科技项目/Science and Technology Project of Guangdong Provincial Communications Department （201502062）；广东省科技计划项目/Science and Technology Planning Project of Guangdong Province（2016A050502006）；中央高校基本科研业务费专项基金/ the Fundamental Research Funds for the Central Universities（2015ZZ008）

An Improved Cell Transmission Model Considering Intersection Factor

YAO Kai-bin, LIN Pei-qun   

  1. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China
  • Received:2016-08-18 Revised:2017-02-09 Online:2017-06-25 Published:2017-06-26

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摘要：

为使元胞传输模型(Cell Transmission Model, CTM)适用于城市道路环境下的交通流仿真，以流量守恒定律和宏观基本图为基础，推导出使用交通流密度描述元胞动态特征的迭代公式，克服了基本CTM中所有元胞长度必须相等的局限性.同时提出了基于车道功能和信号相位的进出口路段和交叉口内部的元胞划分方法，并根据停车线处的放行流率动态调整受信号控制元胞的发送流率，由此提出了考虑信号控制的改进CTM. 最后，分别使用该CTM和VISSIM软件对一个包含2 个交叉口的城市道路进行仿真，并对比分析输出结果.实验表明，两者输出的交通流密度曲线吻合度高，对信号控制交叉口交通流的排队和消散特征的描述十分接近，与此同时，改进CTM显著地减小了计算开销和用时.

关键词: 城市交通, 元胞传输模型, 信号控制, 交通流密度

Abstract:

In order to apply the Cell Transmission Model (CTM) to simulate traffic flow on urban road, iterative formula which describes the dynamic feature of cell using traffic density is deduced based on Flow Conservation Law and Macroscopic Fundamental Diagram, which overcomes limitation of fundamental CTM that all cells must have equal length. Meanwhile, the method to divide cell at entrance and exit of section as well as intersection is proposed based on lane-use assignment and signal phase. The sending rate of signal-controlled cell is adjusted dynamically according to releasing rate at stop-line. Then the improved CTM which considers signal control is proposed. We simulated urban road which contains two intersections using the CTM and VISSIM software respectively and compared outputs finally. Experiment shows that fit degree of two density curves is high and features of queue and dissipation at signalized intersection is approximate. Meanwhile, the improved CTM decreases the computation cost and consuming time obviously.

Key words: urban traffic, cell transmission model, signal control, traffic density

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