Hands-on detection for steering wheels with neural networks

Autor:	Hollmer, Michael, Fischer, Andreas
Rok vydání:	2023
Předmět:	Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	In this paper the concept of a machine learning based hands-on detection algorithm is proposed. The hand detection is implemented on the hardware side using a capacitive method. A sensor mat in the steering wheel detects a change in capacity as soon as the driver's hands come closer. The evaluation and final decision about hands-on or hands-off situations is done using machine learning. In order to find a suitable machine learning model, different models are implemented and evaluated. Based on accuracy, memory consumption and computational effort the most promising one is selected and ported on a micro controller. The entire system is then evaluated in terms of reliability and response time. Comment: Proc. of the Interdisciplinary Conference on Mechanics, Computers and Electrics (ICMECE 2022)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.09044 Zobrazit plný text záznamu View this record from Arxiv