Characterization of driver neuromuscular dynamics for human-automation collaboration design of automated vehicles

Show simple item record

dc.contributor.author Lv, Chen
dc.contributor.author Wang, Huaji
dc.contributor.author Cao, Dongpu
dc.contributor.author Zhao, Yifan
dc.contributor.author Auger, Daniel J.
dc.contributor.author Sullman, Mark
dc.contributor.author Matthias, Rebecca
dc.contributor.author Skrypchuk, Lee
dc.contributor.author Mouzakitis, Alexandros
dc.date.accessioned 2018-04-13T09:10:14Z
dc.date.available 2018-04-13T09:10:14Z
dc.date.issued 2018-03-05
dc.identifier.citation Chen Lv, Huaji Wang, Dongpu Cao et al., Characterization of driver neuromuscular dynamics for human-automation collaboration design of automated vehicles. IEEE/ASME Transactions on Mechatronics, available online 5 April 2018 en_UK
dc.identifier.issn 1083-4435
dc.identifier.uri http://dx.doi.org/10.1109/TMECH.2018.2812643
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/13143
dc.description.abstract In order to design an advanced human-automation collaboration 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 analyzed. In order to identify the key parameters of the driver-steering-wheel interacting system and investigate the system properties under different situations, experiments with driver-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 experimental results, key parameters of the transfer function model are identified by using the Gauss-Newton algorithm. Based on the estimated model with identified parameters, investigation of system properties is then carried out. The characteristics of the driver neuromuscular system are discussed and compared with respect to different steering tasks, hand positions and driver postures. These experimental results with identified system properties provide a good foundation for the development of a haptic take-over control system for automated vehicles. en_UK
dc.language.iso en en_UK
dc.publisher IEEE en_UK
dc.rights Attribution-NonCommercial 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/ *
dc.subject Driver neuromuscular dynamics en_UK
dc.subject driver-vehicle interaction en_UK
dc.subject system identification en_UK
dc.subject automated vehicle en_UK
dc.subject experimental characterization en_UK
dc.title Characterization of driver neuromuscular dynamics for human-automation collaboration design of automated vehicles en_UK
dc.type Article en_UK


Files in this item

The following license files are associated with this item:

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial 4.0 International Except where otherwise noted, this item's license is described as Attribution-NonCommercial 4.0 International

Search CERES


Browse

My Account

Statistics