基于手机信令数据的出行方式识别方法研究
Research on the Recognition Method of Travel Mode Based on Mobile Phone Signaling Data

DOI: 10.12677/OJTT.2020.91001, PP. 1-9

Keywords: 手机信令数据，导航数据，出行方式识别
Mobile Signaling Data, Navigation Data, Recognition of Travel Method

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Abstract:

为了研究手机信令数据在识别用户出行方式领域的应用，进一步提高出行方式识别的准确度。首先，介绍了手机信令数据产生的原理、聚类算法选取的原则。然后，根据地上地下基站的不同将出行方式的识别分为两个方向：地面出行方式、地铁出行的识别。接着，针对地面交通、地铁出行将信令数据分别与导航轨迹数据、地铁基站库数据进行结合建立了模型，以此判定用户的出行方式。最后，基于某运行商提供的志愿者的信令数据对模型进行验证。研究结果表明，该识别算法正确率达86.12%，有效的提升了出行方式识别算法的精度。
In order to study the application of mobile signaling data in the field of identifying user’s travel mode, and improve the accuracy of travel mode identification, firstly, we introduce the principle of signaling data generation, the selection and principle of clustering algorithm. Then, according to the difference between the aboveground and underground base stations, the identification of travel mode can be divided into two directions: the identification of ground travel mode, and the identification of subway. Then, the signaling data is combined with the navigation track data and the base station database data to establish the model for the ground traffic and the subway travel, so as to determine the user’s travel mode. Finally, the model is validated based on the signaling data of volunteers provided by operators. The result shows that the accuracy of the algorithm is 86.12%, which effectively improves the accuracy of the algorithm.

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