交通运输系统工程与信息 ›› 2009, Vol. 9 ›› Issue (4): 66-71 .

• 智能交通系统与信息技术 • 上一篇    下一篇

行程时间噪声数据处理技术研究

刘浩*1,2;张可1;汉克.范少伦2   

  1. 1. 交通部公路科学研究院 国家智能交通系统工程技术研究中心,北京 100088;
    2. 荷兰代尔夫特理工大学,代尔夫特2600 GA
  • 收稿日期:2009-01-17 修回日期:2009-04-23 出版日期:2009-08-25 发布日期:2009-08-25
  • 通讯作者: 刘浩
  • 作者简介:刘浩(1977-),男,四川得昌人,副研究员,荷兰代尔夫特理工大学兼职研究学者.
  • 基金资助:

    国家高技术发展研究计划(863计划)(2006AA11Z206)

Filtering of Travel Time Outliers

LIU Hao 1,2; ZHANG Ke 1; VAN ZUYLEN Henk 2   

  1. 1. National ITS Center, Research Institute of Highway Ministry of Transport, Beijing 100088, China; 2. Delft University of Technology, Delft, 2600GA, The Netherlands
  • Received:2009-01-17 Revised:2009-04-23 Online:2009-08-25 Published:2009-08-25
  • Contact: LIU Hao

摘要: 车牌照匹配技术的广泛应用为行程时间样本数据的精确获取提供了一种可行的方式。但是,由于各种客观原因,采集到的原始数据夹杂着大量的噪声数据,只有剔除了这些噪声数据,行程时间样本数据才能更好地应用于行程时间分析与服务。本文对产生噪声数据的原因进行了详细的分析,回顾了现有的噪声剔除方法,并分析其可能存在的问题;基于交通信息提取计算模型,提出了一种噪声剔除的新方法。以荷兰代尔夫特的一条城市道路为研究对象,基于实际数据对新方法和现有方法进行了对比分析。结果表明,新方法能够更好地剔除噪声数据。

关键词: 交通信息提取计算, 车牌照比对, 行程时间, 噪声剔除

Abstract: With the wide application of license plate matching technology, travel times can be measured with high accuracy. However, there exist tremendous outliers in the raw data due to many reasons. The raw data can be utilized unless the outliers are filtered out. First, this paper investigates the causes of outliers’ production. Then, an overview of existing methods has been conducted to analyze potential problems with those methods. A new method, based on transport information granular computing, is proposed. An urban arterial of Delft, the Netherlands, has been selected as the test site. A comparison between the new method and existing methods has been conducted with the empirical data. The results show that the new method outperforms the existing ones.

Key words: transport information granular computing, license plate matching, travel time, outlier detection

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