Extracting Coach Schedule Information from Massive Trajectory Data

Jun Yu Li, Qingqi Li, Yan Zhu, Yan Ma, Ya’nan Zhou
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Abstract

In view of the difficulties in obtaining nationwide coach schedules, we propose a method of automatically extracting schedule information from massive trajectory data of coaches. We used the Density-Based Spatial Clustering of Applications with Noise algorithm to identify locations of coach stations from the long time-series of historical trajectories, use the application programming interface of online maps to extract station names, and finally extract coach schedules based on multiple trajectories. Experimental results in the Jing-Jin-Ji area validate the effectiveness and accuracy of the proposed method. This method can be used to obtain nationwide coach schedule information in a fast and low cost way.
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从大量轨迹数据中提取教练机时刻表信息
针对目前全国范围内列车时刻表难以获取的问题,提出了一种从大量列车轨迹数据中自动提取列车时刻表信息的方法。利用基于密度的应用噪声空间聚类算法从历史轨迹的长时间序列中识别公交车站的位置,利用在线地图的应用程序编程接口提取车站名称,最后基于多轨迹提取公交时刻表。京津冀地区的实验结果验证了该方法的有效性和准确性。该方法可以快速、低成本地获取全国范围内的航班时刻表信息。
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