Mining urban recurrent congestion evolution patterns from GPS-equipped vehicle mobility data

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• 作者：Shi An ^{anshi@hit.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Haiqiang Yang ^{haiqiang.yang@hotmail.com" class="auth_mail" title="E-mail the corresponding author} ; Jian Wang ; ^{wang_jian@hit.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Na Cui ^{cuina1231@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Jianxun Cui ^{cuijianxun@hit.edu.cn" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Urban road network ; Recurrent congestion ; Congestion evolution pattern ; GPS trajectory data ; Taxi
• 刊名：Information Sciences
• 出版年：2016
• 出版时间：10 December 2016
• 年：2016
• 卷：373
• 期：Complete
• 页码：515-526
• 全文大小：2836 K

文摘

In this study, we developed a method for measuring urban Recurrent Congestion (RC) evolution patterns based on grid divisions and GPS-equipped vehicle mobility data. The method uses a three-step process: Detecting congestion in the grids, distinguishing RC from Non-Recurrent Congestion (NRC), and measuring the RC evolution pattern. A series of indicators were also established which reflect the RC evolution pattern. We conducted an experiment to evaluate the proposed method using GPS trajectory data collected from taxis in Harbin, China, and compared the results against real traffic information and field survey results. We hope that the findings discussed in this paper provide a better understanding of urban RC evolution patterns.