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Unsupervised Driving Profile Detection Using Cooperative Vehicles' Data

机译:使用合作车辆数据进行无监督驾驶轮廓检测

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C-ITS (Cooperative Intelligent Transport Systems) provide nowadays a very huge amounts of data either from vehicles, roadside units, operator servers or smart-phone applications. Data need to be exploited and analyzed. In this paper, we first study the communication logs containing network messages emitted by the vehicles and the infrastructures when they communicate. We used these logs to measure the latency and evaluate if it is consistent with data analysis. Then, we try to detect driving profile using unsupervised machine learning approaches. Results both in terms of latency and of driving profile detection reveal promising issues in this new area.
机译:如今,C-ITS(协作智能运输系统)可以从车辆,路边设备,操作员服务器或智能手机应用程序中提供大量数据。数据需要被利用和分析。在本文中,我们首先研究通信日志,其中包含车辆和基础设施在通信时发出的网络消息。我们使用这些日志来测量延迟并评估其是否与数据分析一致。然后,我们尝试使用无监督的机器学习方法来检测驾驶状况。延迟和驾驶配置文件检测方面的结果都揭示了这一新领域中令人鼓舞的问题。

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