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Characterizing street hierarchies through network analysis and large-scale taxi traffic flow: a case study of Wuhan, China

机译:通过网络分析和大规模出租车交通流量表征街道层次结构:以中国武汉为例

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摘要

Hierarchy is an important property of a street network, which suggests that only a small number of streets are prominent A previous empirical study of a European city has identified four levels of scale in a street network, namely the top 1 %, top 20%, bottom 80%, and bottom 20%. This paper investigates such street hierarchies in a large Asian city, Wuhan, with a complicated network of streets. Based on network analysis, we find that street hierarchies in this case study are slightly different so that the fourth scale is adjusted from the initial 20 to 25%. The detected street hierarchies are further compared to the intensity of large-scale traffic flows at different time scales. We find that distributions of both daily and hourly traffic conform well to the street hierarchies. More specifically, the 20% of top streets accommodate about 98% of traffic flow, and the 1% of top streets account for more than 60% of traffic flow. Moreover, this finding indicates that the current street network of Wuhan needs to be improved because the top 20% of streets are rather overburdened leading to traffic congestion. Our study not only provides new quantitative evidence as to the emergence of street hierarchies but also highlights the possible traffic congestion.
机译:层次结构是街道网络的重要属性,这表明只有很少的街道是突出的。先前对欧洲城市的实证研究确定了街道网络的四个级别的规模,即前1%,前20%,最低80%,最低20%。本文研究了一个亚洲大城市武汉的这种街道层次结构,该城市具有复杂的街道网络。根据网络分析,我们发现本案例研究中的街道层次结构略有不同,因此第四个比例从最初的20%调整为25%。将检测到的街道层次结构与不同时间尺度上的大规模交通流强度进行比较。我们发现,每日流量和每小时流量的分布都非常符合街道层次结构。更具体地说,20%的主要街道可容纳约98%的交通流量,而1%的主要街道则占交通流量的60%以上。此外,该发现表明武汉市目前的街道网络有待改善,因为前20%的街道负担过重,导致交通拥堵。我们的研究不仅为街道层次结构的出现提供了新的定量证据,而且还强调了可能的交通拥堵。

著录项

  • 来源
    《Environment and Planning》 |2016年第2期|276-296|共21页
  • 作者单位

    Wuhan University, State Key Lab Informat Engn Surveying Mapping & R, Peoples R China, Wuhan University of Technology, School of Navigation, Peoples R China;

    Wuhan University, State Key Lab Informat Engn Surveying Mapping & R, Peoples R China, Wuhan Univeristy, Collaborative Innovation Center of Geospatial Technology, Peoples R China,Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, 129 Rd, Wuhan, Hubei, Peoples R China;

    Kent State University, Department of Geography, USA;

    Wuhan University, State Key Lab Informat Engn Surveying Mapping & R, Peoples R China;

    State Grid Corporation of China, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    street hierarchy; network analysis; time-dependent taxi traffic analysis; power laws;

    机译:街道等级;网络分析;随时间变化的出租车交通分析;幂律;

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