The Effect Of Peripheral Visual Feedforward System In Enhancing Situation Awareness And Mitigating Motion Sickness In Fully Automated Driving

Karjanto, Juffrizal and Md. Yusof, Nidzamuddin and Chao, Wang and Terken, Jacques and Delbressine, Frank and Rauterberg, Matthias (2018) The Effect Of Peripheral Visual Feedforward System In Enhancing Situation Awareness And Mitigating Motion Sickness In Fully Automated Driving. Transportation Research Part F: Traffic Psychology And Behaviour, 58. pp. 678-692. ISSN 1369-8478

Text Karjanto (2018) - 1-s2.0-S1369847818300913-main.pdf - Accepted Version Download (1MB)

Abstract

This study investigates the impact of peripheral visual information in alleviating motion sickness when engaging in non-driving tasks in fully automated driving. A peripheral visual feedforward system (PVFS) was designed providing information about the upcoming actions of the automated car in the periphery of the occupant’s attention. It was hypothesized that after getting the information from the PVFS, the users’ situation awareness is improved while motion sickness is prevented from developing. The PVFS was also assumed not to increase mental workload nor interrupt the performance of the non-driving tasks. The study was accomplished on an actual road using a Wizard of Oz technique deploying an instrumented car that behaved like a real fully automated car. The test rides using the current setup and methodology indicated high consistency in simulating the automated driving. Results showed that with PVFS, situation awareness was enhanced and motion sickness was lessened while mental workload was unchanged. Participants also indicated high hedonistic user experience with the PVFS. While providing peripheral information showed positive results, further study such as delivering richer information and active head movement are possibly needed.

Item Type:	Article
Uncontrolled Keywords:	Motion sickness, Situation awareness, Peripheral visual feedforward system, Mental workload, User experience, Fully automated vehicle
Divisions:	Faculty of Mechanical Engineering
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	31 Jul 2019 06:46
Last Modified:	29 Aug 2021 22:52
URI:	http://eprints.utem.edu.my/id/eprint/22984
Statistic Details:	View Download Statistic

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