Evolving cloud-based system for the recognition of drivers actions. Skrjanc, I., Andonovski, G., Ledezma, A., Sipele, O., Iglesias, J. A., & Sanchis, A. Expert Systems with Applications, 2017. ![Evolving cloud-based system for the recognition of drivers actions [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Abstract 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.
@article{Skrjanc2017ESwA,
title = "Evolving cloud-based system for the recognition of drivers actions",
journal = "Expert Systems with Applications",
year = "2017",
issn = "0957-4174",
doi = "https://doi.org/10.1016/j.eswa.2017.11.008",
url = "http://www.sciencedirect.com/science/article/pii/S0957417417307583",
author = "Igor Skrjanc and Goran Andonovski and Agapito Ledezma and Oscar Sipele and Jose Antonio Iglesias and Araceli Sanchis",
keywords = "Evolving systems, Beheviour recognition, Expert system, Cluster",
abstract = "Abstract 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."
}
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