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Remote Driver Identification Using Minimal Sensory Data

机译:使用最少的感官数据进行远程驾驶员识别

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摘要

This letter proposes a driver identification algorithm developed for using minimal information transmitted in vehicle-to-vehicle (V2V) environment based on the assumption that each driver has his/her own unique driving behavior characteristics hidden in conventional driving behaviour signals. Performance evaluation using real-world data shows that the proposed algorithm accurately identifies three drivers in 15 trips using only two acceleration signals at a sampling rate much lower than the one used in previous study. Furthermore, it is shown that the proposed algorithm is able to perform driver identification within a small connectivity time in a scenario where driving behavior signals of are transmitted via a V2V communication environment in a streaming manner.
机译:这封信提出了一种驾驶员识别算法,该算法基于每个驾驶员在常规驾驶行为信号中隐藏了自己独特的驾驶行为特征的假设而开发,以使用在车辆到车辆(V2V)环境中传输的最少信息。使用实际数据进行的性能评估表明,提出的算法仅使用两个加速度信号就可以在15个行程中准确地识别出三个驾驶员,而采样率远低于先前研究中使用的采样率。此外,示出了所提出的算法能够在以流方式经由V2V通信环境发送驾驶行为信号的情况下,在短的连接时间内执行驾驶员识别。

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