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首页> 外文会议>COTA international conference of transportation professionals >Identification of Taxi Pick-Up and Drop-Off Hotspots Using the Density-Based Spatial Clustering Method
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Identification of Taxi Pick-Up and Drop-Off Hotspots Using the Density-Based Spatial Clustering Method

机译：基于密度的空间聚类方法识别出租车接送热点

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摘要

The taxi is a common way of travelling in cities, which is an important supplement to other public travel modes. Thus, it is necessary to understand the characters of taxi operation and its passengers. The individual vehicle trajectory information has been obtained easily and economically because of the widely-used GPS devices, which makes mining the meaningful information behind the trajectory feasible and more convenient. In this paper, the taxi GPS data from Kunshan City, in China, is used to identify the pick-up and drop-off hotspots. Firstly, a procedure is proposed to extract the taxi trip trajectories from the vast amounts of GPS data. Then, with the help of data mining technology, the pick-up and drop-off hotspots are analyzed using the density-based spatial clustering method. It comes to a conclusion that the pick-up and drop-off hotspots can share a similar distribution pattern and overlap very well.
机译：出租车是城市中常见的出行方式，是对其他公共出行方式的重要补充。因此，有必要了解出租车运营及其乘客的特征。由于使用了广泛的GPS设备，可以轻松而经济地获得单个车辆的轨迹信息，这使得在轨迹后面挖掘有意义的信息变得可行且更加方便。本文使用来自中国昆山市的出租车GPS数据来识别上下车热点。首先，提出了一种从大量GPS数据中提取出租车行程轨迹的程序。然后，借助数据挖掘技术，使用基于密度的空间聚类方法来分析上下车热点。得出的结论是，接送热点可以共享类似的分布模式，并且可以很好地重叠。

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