城市主干道交通拥堵原因识别方法

Xiaoxi Cai, Yanping Xiao, Zhang Lei
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引用次数: 0

摘要

识别拥堵原因是解决交通拥堵的关键。为了提高拥堵控制的效率,本文建立了基于模式识别、拥堵源追踪和拥堵原因判别三个阶段的拥堵原因识别方法。提出了 K-means 算法,计算重复性拥堵的频率阈值,根据拥堵传播时序规律追溯拥堵源,基于因果逻辑关系构建拥堵故障树,并利用专家评分法和云模型确定各原因的发生概率和重要性。测试结果表明,该方法前景广阔,可为科学控制拥塞提供支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic Congestion Cause Identification Method for Urban Main Roads
Identifying the causes of congestion is the key to solving traffic congestion. To improve the efficiency of congestion control, this paper establishes a congestion cause identification method based on the three stages of pattern recognition, source tracing, and cause discrimination. The K-means algorithm was proposed to calculate the frequency threshold of recurrent congestion, trace the sources of congestion according to the rules of congestion propagation time sequences, build a congestion fault tree based on causal logic relationships, and determine the occurrence probability and importance of each cause by using the expert scoring method and cloud model. The test results showed that the method is promising and could provide support for scientific congestion control.
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