COMING SOON! PQDT Open is getting a new home!

ProQuest Open Access Dissertations & Theses will remain freely available as part of a new and enhanced search experience at

Questions? Please refer to this FAQ.

Dissertation/Thesis Abstract

Joint Simon Effect with Mixed Automation
by Taylor, Anika Elizabeth, M.S., California State University, Long Beach, 2020, 51; 28151686
Abstract (Summary)

The concept of driverless cars is not too far off in the future. Therefore, research examining how people interact with mixed automation is necessary in order to mediate any possible negative effects of such interactions. The current study investigates possible compatibility effects of a human actor and mixed automation as a co-actor in the context of driving. For this study, I used a modified joint Simon task, where a human participant performs the task while cooperatively driving with a mixed automated driving simulator. The purpose of this experiment is to determine whether people represent and monitor automation in a shared task. This may be important because many drivers use systems such as advanced driver-assistance systems (ADAS), which require the driver to share tasks with automation. Therefore, it is important to know if people are paying attention to the ADAS for situations in which the systems make a mistake, thus requiring the driver to take over.

Indexing (document details)
Advisor: Miles, James D.
Commitee: Vu, Kim-Phuong L., Strybel, Thomas Z.
School: California State University, Long Beach
Department: Psychology
School Location: United States -- California
Source: MAI 82/8(E), Masters Abstracts International
Subjects: Psychology
Keywords: Advanced driver-assistance systems (ADAS), Compatibility effects, Joint Simon effect, Mixed automation
Publication Number: 28151686
ISBN: 9798582504252
Copyright © 2021 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy