Evolution Regularity Mining and Gating Control Method of Urban Recurrent Traffic Congestion: A Literature Review
Evolution Regularity Mining and Gating Control Method of Urban Recurrent Traffic Congestion: A Literature Review
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城市重复性交通拥堵演化规律挖掘及门控控制方法研究综述
DOI：
10.1155/2020/5261580
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发表时间：
2020-01
影响因子：
2.3
通讯作者：
Changxi Ma;Jibiao Zhou;X. Xu;Jin Xu
中科院分区：
文献类型：
--
作者：
Changxi Ma;Jibiao Zhou;X. Xu;Jin Xu
为了解城市经常性交通拥堵的现状，从交通拥堵识别、演变趋势预测、城市路网门控三个方面回顾了当前城市经常性交通拥堵和门控的研究成果。目前的研究主要分为三个方面：(a)目前的研究大多基于历史数据的统计分析，而拥堵识别则是通过获取小规模的交通参数来进行。因此，缺乏对城市全球道路网的拥堵研究。在未解决拥堵形式之前，无法识别情况并未能有效警告甚至避免交通拥堵； (b) 对城市路网拥堵的相关性研究不足，特别是在深度学习方面，以及考虑时空相关性进行拥堵演变趋势预测方面； （三）缺乏定量研究方法、动态确定闸控区域以及消除交通拥堵的有效对策。针对当前研究的不足，提出了未来可以进一步探索的六个研究方向。
To understand the status quo of urban recurrent traffic congestion, the current results of recurrent traffic congestion, and gating control are reviewed from three aspects: traffic congestion identification, evolution trend prediction, and urban road network gating control. Three aspects of current research are highlighted: (a) The majority of current studies are based on statistical analyses of historical data, while congestion identification is performed by acquiring small-scale traffic parameters. Thus, congestion studies on the urban global roadway network are lacking. Situation identification and the failure to effectively warn or even avoid traffic congestion before congestion forms are not addressed; (b) correlation studies on urban roadway network congestion are inadequate, especially regarding deep learning, and considering the space-time correlation for congestion evolution trend prediction; and (c) quantitative research methods, dynamic determination of gating control areas, and effective countermeasures to eliminate traffic congestion are lacking. Regarding the shortcomings of current studies, six research directions that can be further explored in the future are presented.