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Evolving cloud-based system for the recognition of drivers' actions

机译:不断发展的基于云的系统,用于识别驾驶员的行为

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This paper presents an evolving cloud-based algorithm for the recognition of drivers' actions. The general idea is to detect different manoeuvres by processing the standard signals that are usually measured in a car, such as the speed, the revolutions, the angle of the steering wheel, the position of the pedals, and others, without additional intelligent sensors. The primary goal of this investigation is to propose a concept that can be used to recognise various driver actions. All experiments are performed on a realistic car simulator. The data acquired from the simulator are pre-processed and then used in the evolving cloud-based algorithm to detect the basic elementary actions, which are then combined in a prescribed sequence to create tasks. Finally, the sequences of different tasks form the most complex action, which is called a manoeuvre. As shown in this paper, the evolving cloud-based algorithm can be very efficiently used to recognise the complex driver's action from raw signals obtained by typical car sensors. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文提出了一种基于云的不断发展的算法,用于识别驾驶员的动作。总体思路是通过处理通常在汽车中测量的标准信号来检测不同的操作,例如速度,转数,方向盘角度,踏板位置等,而无需其他智能传感器。这项调查的主要目的是提出一种可用于识别各种驾驶员动作的概念。所有实验均在真实的汽车模拟器上进行。从模拟器获取的数据经过预处理,然后用于基于云的不断发展的算法中,以检测基本的基本操作,然后按规定的顺序进行组合以创建任务。最后,不同任务的序列形成最复杂的动作,称为动作。如本文所示,基于云的不断发展的算法可以非常有效地用于从典型的汽车传感器获得的原始信号中识别复杂驾驶员的动作。 (C)2017 Elsevier Ltd.保留所有权利。

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