东北大学学报:自然科学版 ›› 2015, Vol. 36 ›› Issue (11): 1530-1534.DOI: 10.12068/j.issn.1005-3026.2015.11.003

• 信息与控制 • 上一篇    下一篇

基于GPS轨迹数据的拥堵路段预测

林树宽, 于伶姿, 乔建忠, 张百合   

  1. (东北大学 信息科学与工程学院, 辽宁 沈阳110819)
  • 收稿日期:2014-10-23 修回日期:2014-10-23 出版日期:2015-11-15 发布日期:2015-11-10
  • 通讯作者: 林树宽
  • 作者简介:林树宽(1966-),女,吉林长春人,东北大学教授; 乔建忠(1964-),男,辽宁兴城人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(61272177).

The Congestion Road Segment Prediction Based on GPS Trajectory Data

LIN Shu-kuan, YU Ling-zi, QIAO Jian-zhong, ZHANG Bai-he   

  1. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China.
  • Received:2014-10-23 Revised:2014-10-23 Online:2015-11-15 Published:2015-11-10
  • Contact: LIN Shu-kuan
  • About author:-
  • Supported by:
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摘要: 基于真实的GPS轨迹数据,对城市拥堵路段进行预测.在此过程中,摒弃传统的基于交通流预测和拥堵识别的方法,提出一种新的基于拥堵向量和拥堵转移矩阵的拥堵路段预测方法.该方法同时考虑路段拥堵的时间周期性和时空相关性,通过对出租车GPS轨迹数据进行挖掘和训练,建立拥堵向量和拥堵转移矩阵,实现对拥堵路段的预测.真实数据集上的实验验证了所提的拥堵路段预测方法的有效性.

关键词: GPS轨迹数据, 路段间时空因果关系, 拥堵转移概率, 拥堵转移矩阵, 拥堵路段预测

Abstract: Congestion road segments over real GPS trajectory data was predicted. The traditional methods were ostracized based on traffic flow prediction and congestion identification, and a novel method was proposed based on the congestion vector and the congestion transition matrix. The congestion vector and the congestion transition matrix were established by mining and training taxi GPS trajectory data, resulting in the implementation of the prediction of traffic congestion. In the course of prediction, time periodicity and spatial-temporal correlation of road segment congestion were both considered. The experiments on real data show the effectiveness of the congestion road segment prediction method proposed.

Key words: GPS trajectory data, spatial-temporal causal relationship between road segments, congestion transition probability, congestion transition matrix, congestion road segment prediction

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