Real-time identification of probe vehicle trajectories in the mixed traffic corridor
作者: Yu MeiKeshuang TangKeping Li
作者单位: 1Department of Comprehensive Transportation Information and Control Engineering, Tongji University, No. 4800, Cao’an Road, Shanghai 201804, China
刊名: Transportation Research Part C, 2015, Vol.57 , pp.55-67
来源数据库: Elsevier Journal
DOI: 10.1016/j.trc.2015.06.008
关键词: Semi-supervised learning techniqueProbe vehicle trajectoryMixed corridorUrban expressway
英文摘要: Abstract(#br)This paper proposes three enhanced semi-supervised clustering algorithms, namely the Constrained-K-Means (CKM), the Seeded-K-Means (SKM), and the Semi-Supervised Fuzzy c-Means (SFCM), to identify probe vehicle trajectories in the mixed traffic corridor. The proposed algorithms are able to take advantage of the strengthens of topological relation judgment and the semi-supervised learning technique by optimizing the selection of pre-labeling samples and initial clustering centers of the original semi-supervised learning technique based on horizontal Global Positioning System data. The proposed algorithms were validated and evaluated based on the probe vehicle data collected at two mixed corridors on Shanghai’s urban expressways. Results indicate that the enhanced SFCM algorithm...
全文获取路径: Elsevier  (合作)
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关键词翻译
关键词翻译
  • 探针 灭草定
  • corridor 走廊
  • vehicle 
  • learning 学识
  • trajectory 轨道
  • mixed 混合的
  • expressway 高速公路
  • Probe 灭草定
  • probe 灭草定
  • traffic 话务量
  • identification 辨认