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首页> 外文期刊>Intelligent Transport Systems, IET >Mining taxi trajectories for most suitable stations of sharing bikes to ease traffic congestion
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Mining taxi trajectories for most suitable stations of sharing bikes to ease traffic congestion

机译：为最适合共享自行车的站点挖掘出租车轨迹，以缓解交通拥堵

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摘要

Sharing bike service is a new emerging public transportation, which has been the hottest topic for months. Sharing bike service provides flexible demand-oriented transit services for city commuters. However, as large amount of sharing bikes flood into big cities, problems caused by chaotic order of sharing bikes are emerging slowly. The authors aim to draw support from taxi trajectories to analyse current traffic condition and improve it with sharing bikes. In this study, the authors propose a traffic congestion finding framework, called CF. In CF, derived from the points density-based clustering method of inspiration, the authors propose a new clustering method (CF-Dbscan) and successfully applied it to the clustering of trajectories. A road network matching algorithm (CF-Matching) helps to match GPS points to road net even if points are in low-sampling-rate. They also employ a ranking feedback mathematical model to adjust the number of sharing bikes of different stations to meet people's demand and reduce redundancy. The first experiment proves that the proposed clustering algorithm performs better than traditional DBSCAN. Another experiment is conducted to verify the effectiveness of the proposed framework in reducing traffic congestion. The experimental results prove that with the proposed framework the authors can achieve the purpose of easing traffic congestion.
机译：共享自行车服务是一种新兴的公共交通，这已成为数月来最热门的话题。共享单车服务为城市通勤者提供了灵活的，面向需求的过境服务。但是，随着大量的共享单车涌入大城市，共享单车的混乱秩序所引起的问题正在逐渐显现。作者的目的是从滑行轨迹中获得支持，以分析当前的交通状况并通过共享自行车来改善这种状况。在这项研究中，作者提出了一种交通拥堵发现框架，称为CF。在CF中，从基于点密度的启发式聚类方法中获得了灵感，作者提出了一种新的聚类方法（CF-Dbscan），并将其成功地应用于轨迹聚类。道路网匹配算法（CF-Matching）有助于将GPS点与路网匹配，即使这些点的采样率较低。他们还采用排名反馈数学模型来调整不同站点的共享单车数量，以满足人们的需求并减少冗余。第一个实验证明了该聚类算法的性能优于传统的DBSCAN。进行了另一个实验，以验证所提出的框架在减少交通拥堵方面的有效性。实验结果证明，通过提出的框架，作者可以达到缓解交通拥堵的目的。

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  • 来源
    《Intelligent Transport Systems, IET》 |2018年第7期|586-593|共8页
  • 作者

    Weipeng Jing; Jian Kang; Meiling Liu;

  • 作者单位

    College of Information and Computer Engineering, Northeast Forestry University, People's Republic of China;

    College of Information and Computer Engineering, Northeast Forestry University, People's Republic of China;

    College of Information and Computer Engineering, Northeast Forestry University, People's Republic of China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    bicycles; road traffic; transportation;

    机译：自行车;道路交通;运输;

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