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Research on traffic congestion characteristics of city business circles based on TPI data: The case of Qingdao, China

机译:基于TPI数据的城市商业界交通拥堵特征研究:中国青岛的案例

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摘要

This study aims to investigate the congestion of the urban business circle based on traffic performance index (TPI) data. A hierarchical clustering algorithm is adopted for the data analysis. A dataset of nearly 64,260 pieces of TPI data from July to October 2017 in Qingdao is collected, and its features, such as interval characteristics, mean time distribution and spatiotemporal correlation, are analyzed. The results show that the southern coastal commercial circle of Qingdao is more congested than the other circles; there exists a morning and afternoon peak, with two peaks on workdays; otherwise, weekend and vacation periods do not show congestion. The congestion level toward the end of the vacation week (October 4th-8th) is lower than that during the beginning (October 1st-3rd). Considering the temporal and spatial dimensions, the causes of the two different congestion states during the holidays are speculated upon The characteristics of traffic congestion in Qingdao business circle and its possible causes are proposed, and a new design and overall plan for Qingdao is promoted. (C) 2019 Elsevier B.V. All rights reserved.
机译:本研究旨在根据交通绩效指数(TPI)数据来调查城市商业圈的拥堵。采用分层聚类算法进行数据分析。收集了近64,260件TPI数据的数据集,在青岛收集了近64,260件TPI数据,分析了其特征,如间隔特征,平均时间分布和时空相关性。结果表明,青岛南部沿海商业圈比其他圈子更拥挤;有一个早晨和下午的峰值,工作日有两个峰值;否则,周末和假期不显示拥堵。在休假周(10月4日 - 8日)结束时的拥堵水平低于开始期间(10月1日 - 第3次)。考虑到时间和空间尺寸,假期期间两种不同拥堵状态的原因拨现了青岛商业圈交通拥堵的特点,提出了可能的原因,促进了青岛的新设计和整体计划。 (c)2019 Elsevier B.v.保留所有权利。

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