一种宏微观结合的主干路交通流状态分类方法  

A Macroscopic and Microscopic Classification Method for Traffic Flow State of Trunk Road

作　　者：张小丽[1] 郭志勇[2] 李红伟[1] 周云月 ZHANG Xiaoli;GUO Zhiyong;LI Hongwei;ZHOU Yunyue(College of Civil and Transportation Engineering,Hohai University,Nanjing 210098,China;School of Transportation and Logistics Engineering,Wuhan University of Technology,Wuhan 430070,China;Zhuji Department of Transportation,Shaoxing 311800,China)

机构地区：[1]河海大学土木与交通学院,南京210098 [2]武汉理工大学交通与物流工程学院,武汉430070 [3]诸暨市交通运输局,绍兴311800

出　　处：《武汉理工大学学报（交通科学与工程版）》2021年第6期1022-1028,共7页Journal of Wuhan University of Technology（Transportation Science & Engineering）

基　　金：国家自然科学基金(51608171,71501061);江苏省自然科学基金(BK20150821)。

摘　　要：针对现有交通流状态分类方法所用参数较单一,不能捕捉城市主干道交通流阻断特点的问题,提出了同时考虑交通流宏微观信息的城市主干路交通流状态划分方法.该方法在对速度进行k-means聚类得到初始交通流状态基础上,基于车头时距微观交通参数使用相对速度绝对值法进行进一步划分.最终交通流被划分为畅通自由流、稳定自由流、稳定跟驰和拥堵跟驰四个状态.通过与常用方法对比发现,所提出方法不仅能得到各交通状态的确切阈值,也更符合城市主干路交通流的运行特征.Aiming at the problem that the existing traffic flow state classification methods can’t capture the traffic flow blocking characteristics of urban trunk roads with single parameters,a traffic flow state classification method of urban trunk roads considering both macro and micro information of traffic flow was proposed.Based on the initial traffic flow state obtained by K-means clustering of speed,this method used the absolute value method of relative speed to further divide it based on microscopic traffic parameters of headway.The final traffic flow was divided into four states:smooth free flow,stable free flow,stable car-following and congestion car-following Compared with common methods,it is found that the proposed method can not only get the exact threshold of each traffic state,but also accord with the operation characteristics of urban trunk road traffic flow.

关 键 词：交通工程 交通状态划分 聚类 阻断交通流 车头时距 速度 

分 类 号：U491.114[交通运输工程—交通运输规划与管理]