工业工程 ›› 2020, Vol. 23 ›› Issue (1): 1-9.doi: 10.3969/j.issn.1007-7375.2020.01.001

• 专题论述 •    下一篇

面向宏观基本图的多模式交通路网分区算法

傅惠1, 王叶飞1, 陈赛飞2   

  1. 1. 广东工业大学 机电工程学院, 广东 广州 510006;
    2. 澳门科技大学 系统工程研究所, 澳门特别行政区 999078
  • 收稿日期:2019-10-14 发布日期:2020-02-21
  • 作者简介:傅惠(1981-),男,湖北省人,教授,博士,主要研究方向为大数据、系统建模与仿真优化
  • 基金资助:
    国家自然科学基金资助项目(61573110);广东省科技计划资助项目(2016B010127004)

A Partitioning Algorithm of Multimodal Traffic Networks for Obtaining Macroscopic Fundamental Diagram

FU Hui1, WANG Yefei1, CHEN Saifei2   

  1. 1. School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China;
    2. Macau Institute of Systems Engineering, Macau University of Science and Technology, Macau 999078, China
  • Received:2019-10-14 Published:2020-02-21

摘要: 为探究不同模式交通流之间的相互作用关系,提出一种考虑路网多模式属性的分区算法。以社会车和公交车速度和路段邻接关系为划分依据,提出初始子区划分、子区合并、子区边界调整的三步分区算法。以深圳多模式交通数据为例进行了子区划分实验,结果表明本文算法相较于其他分区算法能得到两种模式异质性都较低的交通小区;通过识别路网子区中的多模式宏观基本图,验证了实际交通路网中存在多模式宏观基本图。

关键词: 城市交通, 分区算法, 宏观基本图, 多模式网络, 交通流

Abstract: For revealing the interaction between different modes of traffic flow, this paper proposes a network partitioning algorithm considering the multi-mode attributes of the given road network. Considering speed of social vehicles and buses and adjacent matrix of road segments in real network, a three-step framework for network partitioning is proposed which consists of initialized partitioning, subnetwork merging, and boundary adjustment. Various numerical experiments are conducted using real data of Shenzhen road network. The results show that the heterogeneity degree of the partitioned network using the proposed three-step partitioning algorithm are lower than the previous method. In addition, the existence of the multi-mode macroscopic fundamental diagram (MFD) is verified by recognizing the corresponding macroscopic density to flow relationship in the real subnetworks of Shenzhen. Therefore, the proposed algorithm can be used to achieve a well-defined MFD of certain targeted subnetwork.

Key words: urban traffic, partitioning algorithm, macroscopic fundamental diagram, multimodal network, traffic flow

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