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Data mining tools for real-time traffic signal decision support maintenance

机译:数据挖掘工具,用于实时交通信号决策支持和维护

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This paper describes research investigating the application of data mining tools to aid in the development of traffic signal timing plans. A case study was conducted to illustrate that the use of hierarchical cluster analysis can be used to automatically identify time-of-day (TOD) intervals,, based on the data, that support the design of a TOD signal control system. The cluster analysis approach is able to utilize a high-resolution system state, definition that takes full advantaged of the extensive set of sensors deployed in a traffic signal system and cluster validation supports the hypotheses presented. The results of this research indicate that advanced data mining techniques hold high potential to provide automated signal control techniques.
机译:本文描述了研究调查数据挖掘工具的应用,以协助交通信号定时计划的发展。进行了一个案例研究,以说明可以使用分层聚类分析基于数据自动识别支持TOD信号控制系统设计的时间间隔(TOD)。聚类分析方法能够利用高分辨率的系统状态,该定义充分利用了部署在交通信号系统中的大量传感器,并且聚类验证支持了所提出的假设。这项研究的结果表明,先进的数据挖掘技术具有提供自动化信号控制技术的巨大潜力。

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