Characterisation of driver neuromuscular dynamics for haptic take-over system design for automated vehicles

Characterisation of driver neuromuscular dynamics for haptic take-over system design for automated vehicles
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DOI:
10.1109/iecon.2017.8216786
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发表时间:
2017-10
期刊:
IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
影响因子:
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通讯作者:
Chen Lv;Huaji Wang;Dongpu Cao;Yifan Zhao;D. Auger;M. Sullman;R. Matthias;L. Skrypchuk;A. Mouzakitis
Chen Lv;Huaji Wang;Dongpu Cao;Yifan Zhao;D. Auger;M. Sullman;R. Matthias;L. Skrypchuk;A. Mouzakitis
中科院分区:
其他
文献类型:
--
作者:
Chen Lv;Huaji Wang;Dongpu Cao;Yifan Zhao;D. Auger;M. Sullman;R. Matthias;L. Skrypchuk;A. Mouzakitis

文献摘要

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为了开发高度自动化车辆的先进触觉接管系统,需要对驾驶员的神经肌肉动力学进行研究。本文首先建立了驾驶员与方向盘神经肌肉相互作用的动力学模型。分析了系统的传递函数和固有频率。为了确定驾驶员-方向盘耦合系统的关键参数,研究不同工况下的系统性能,进行了环内驱动实验。对于每个测试对象,指示完成两个转向任务,即被动转向任务和主动转向任务。此外,在实验过程中,受试者以两种不同的姿势和三种不同的手位操纵方向盘。根据试验结果,确定并研究了传递函数的关键参数和系统性能。讨论了驾驶员神经肌肉系统的数据和特征,并就不同的转向任务、手的位置和驾驶员的姿势进行了比较。这些测试结果确定了系统性能,为开发用于自动驾驶车辆的触觉接管控制系统提供了良好的基础。
In order to develop an advanced haptic take-over system for highly automated vehicles, research into the driver's neuromuscular dynamics is needed. In this paper a dynamic model of drivers' neuromuscular interaction with a steering wheel is firstly established. The transfer function and the natural frequency of the systems are analysed. In order to identify the key parameters of the driver-steering-wheel coupled system and investigate the system properties under different situations, experiments with drive-in-the-loop are carried out. For each test subject, two steering tasks, namely the passive and active steering tasks, are instructed to be completed. Furthermore, during the experiments, subjects manipulated the steering wheel with two distinct postures and three different hand positions. Based on the test results, key parameters of the transfer function and system properties are identified and investigated. The data and characteristics of the driver neuromuscular system are discussed and compared with respect to different steering tasks, hand positions and driver postures. These test results identified system properties that provide a good foundation for the development of a haptic take-over control system for automated vehicles.