Detection of clusters in traffic networks based on spatio‐temporal flow modeling

Shi Yan; Deng Min; Gong Jianya; Lu Chang‐Tien; Yang Xuexi; Liu Huimin

摘要

Abstract >Spatio‐temporal clustering is a highly active research topic and a challenging issue in spatio‐temporal data mining. Many spatio‐temporal clustering methods have been designed for geo‐referenced time series. Under some special circumstances, such as monitoring traffic flow on roads, existing methods cannot handle the temporally dynamic and spatially heterogeneous correlations among road segments when detecting clusters. Therefore, this article develops a spatio‐temporal flow‐based approach to detect clusters in traffic networks. First, a spatio‐temporal flow process is modeled by combining network topology relations with real‐time traffic status. On this basis, spatio‐temporal neighborhoods are captured by considering traffic time‐series similarity in spatio‐temporal flows. Spatio‐temporal clusters are further formed by successive connection of spatio‐temporal neighbors. Experiments on traffic time series of central London's road network on both weekdays and weekends are performed to demonstrate the effectiveness and practicality of the proposed method. </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><abstract type =“main”xml：id =“tgis12521-abs-abs-0001”xml：lang =“en”> <title type =“main”>抽象</ title> >时空群集是一个高度活动时空数据挖掘研究主题与挑战性问题。许多时空聚类方法是为地理参考时间序列设计的。在一些特殊情况下，例如监控道路上的交通流量，现有方法无法在检测群集时处理道路段之间的时间动态和空间异构相关性。因此，本文开发了一种基于时空流的方法来检测交通网络中的群集。首先，通过将网络拓扑关系与实时流量状态组合来建模时空流程。在此基础上，通过考虑时空流动中的交通时间序列相似性来捕获时空邻域。通过连续连接的时空邻居进一步形成时空簇。在平日和周末进行伦敦市中心道路网络交通时间系列的实验，以证明所提出的方法的有效性和实用性。</ p> </摘要> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-31674/'>《Transactions in GIS: TG》</a> <b style="margin: 0 2px;">|</b><span>2019年第2期</span><b style="margin: 0 2px;">|</b><span>共22页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Shi Yan&option=202" target="_blank" rel="nofollow">Shi Yan;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Deng Min&option=202" target="_blank" rel="nofollow">Deng Min;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Gong Jianya&option=202" target="_blank" rel="nofollow">Gong Jianya;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Lu Chang‐Tien&option=202" target="_blank" rel="nofollow">Lu Chang‐Tien;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Yang Xuexi&option=202" target="_blank" rel="nofollow">Yang Xuexi;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Liu Huimin&option=202" target="_blank" rel="nofollow">Liu Huimin;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>Department of Geo‐informaticsCentral South UniversityChangsha China;</p> <p>Department of Geo‐informaticsCentral South UniversityChangsha China;</p> <p>State Key Laboratory of Information Engineering in Surveying Mapping &</p> <p>Remote SensingWuhan UniversityWuhan China;</p> <p>Department of Computer ScienceVirginia TechFalls Church Virginia USA;</p> <p>Department of Geo‐informaticsCentral South UniversityChangsha China;</p> <p>Department of Geo‐informaticsCentral South UniversityChangsha China;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/4940.html" title="测绘数据库与信息系统">测绘数据库与信息系统;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> </p> </li> </ul> </div> </div> <div class="literature cardcommon" id="literaturereference" style="display:none"> <div class="similarity "> <h3 class="all_title" id="enpatent111">引文网络</h3> <div class="referencetab clearfix"> <ul id="referencedaohang"> <li dataid="referenceul">参考文献</li> <li dataid="citationul">引证文献</li> <li dataid="commonreferenceul">共引文献</li> <li dataid="commoncitationul">同被引文献</li> <li dataid="tworeferenceul">二级参考文献</li> <li dataid="twocitationul">二级引证文献</li> </ul> </div> <div class="reference_details" id="referenceList"> <ul id="referenceul"></ul> <ul id="citationul"></ul> <ul id="commonreferenceul"></ul> <ul id="commoncitationul"></ul> <ul id="tworeferenceul"></ul> <ul id="twocitationul"></ul> </div> </div> </div> <div class="literature cardcommon"> <div class="similarity "> <h3 class="all_title" id="enpatent66">相似文献</h3> <div class="similaritytab clearfix"> <ul> <li class="active" >外文文献</li> <li >中文文献</li> <li >专利</li> </ul> </div> <div class="similarity_details"> <ul > <li> <div> <b>1. </b><a class="enjiyixqcontent" href="/journal-foreign-detail/0704024965674.html">Detection of clusters in traffic networks based on spatio‐temporal flow modeling</a> <b>[J]</b> . <span> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Shi Yan&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">Shi 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