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Application of locally weighted regression-based approach in correcting erroneous individual vehicle speed data

机译:基于局部加权回归的方法在修正错误的单个车速数据中的应用

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摘要

Because of the quality of raw data being an essential feature in determining the reliability of traffic information, an effective detection and correction of outliers in raw field-collected traffic data has been an interest for many researchers. Global positioning systems (GPS)-based traffic surveillance systems are capable of producing individual vehicle speeds that are vital for transportation researchers and practitioners in traffic management and information strategies. This study proposes a locally weighted regression (LWR)-based filtering method for individual vehicle speed data. To fully and systematically evaluate this proposed method, a technique to generate synthetic outliers and two approaches to inject synthetic outliers are presented. Parameters that affect the smoothing performance associated with LWR are devised and applied to obtain a more robust and reliable data correction method. For a comprehensive performance evaluation of the developed LWR method, comparisons to exponential smoothing (ES) and autoregressive integrated moving average (ARIMA) methods were conducted. Because the LWR-based filtering method outperformed both the ES and ARIMA methods, this study showed its useful benefits in filtering individual vehicle speed data. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译:由于原始数据的质量是确定交通信息可靠性的基本特征,因此有效地检测和校正原始现场采集的交通数据中的异常值已成为许多研究人员关注的问题。基于全球定位系统(GPS)的交通监控系统能够产生单独的车速,这对于交通管理和信息策略中的交通研究人员和从业人员至关重要。这项研究针对单个车速数据提出了一种基于局部加权回归(LWR)的滤波方法。为了全面,系统地评估此提议的方法,提出了一种生成合成异常值的技术和两种注入合成异常值的方法。设计并应用了影响与LWR相关的平滑性能的参数,以获得更鲁棒和可靠的数据校正方法。为了对已开发的LWR方法进行综合性能评估,将其与指数平滑(ES)方法和自回归综合移动平均(ARIMA)方法进行了比较。由于基于LWR的过滤方法优于ES方法和ARIMA方法,因此本研究显示了其在过滤单个车速数据中的有用好处。版权所有(c)2015 John Wiley&Sons,Ltd.

著录项

  • 来源
    《Journal of Advanced Transportation》 |2016年第2期|180-196|共17页
  • 作者单位

    Hanyang Univ Ansan, Dept Transportat & Logist Engn, 55 Hanyangdaehak Ro, Ansan 426791, Kyunggi Do, South Korea;

    Villanova Univ, Villanova Ctr Adv Sustainabil Engn, Dept Civil & Environm Engn, 800 E Lancaster Ave, Villanova, PA 19085 USA;

    Hanyang Univ Ansan, Dept Transportat & Logist Engn, 55 Hanyangdaehak Ro, Ansan 426791, Kyunggi Do, South Korea;

    Univ Calif Irvine, Inst Transportat Studies, Irvine, CA 92697 USA|Univ Calif Irvine, Dept Civil & Environm Engn, Irvine, CA 92697 USA;

    KBS Media Ctr, Korea Maritime Inst, Maritime Ind & Logist Div, Maritime Policy & Safety Dept, 16F,Maebongsan Ro 45, Seoul 121270, South Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    outlier detection; data correction; locally weighted regression (LWR); global positioning system (GPS);

    机译:异常检测;数据校正;局部加权回归(LWR);全球定位系统(GPS);
  • 入库时间 2022-08-18 01:11:46

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