Title

Impact Of Automation And Task Load On Unmanned System Operator'S Eye Movement Patterns

Keywords

Adaptive automation; Eye tracking; Unmanned ground systems; Workload

Abstract

Eye tracking under naturalistic viewing conditions may provide a means to assess operator workload in an unobtrusive manner. Specifically, we explore the use of a nearest neighbor index of workload calculated using eye fixation patterns obtained from operators navigating an unmanned ground vehicle under different task loads and levels of automation. Results showed that fixation patterns map to the operator's experimental condition suggesting that systematic eye movements may characterize each task. Further, different methods of calculating the workload index are highly correlated, r(46) = .94, p = .01. While the eye movement workload index matches operator reports of workload based on the NASA TLX, the metric fails on some instances. Interestingly, these departure points may relate to the operator's perceived attentional control score. We discuss these results in relation to automation triggers for unmanned systems. © 2009 Springer.

Publication Date

12-1-2009

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

5638 LNAI

Number of Pages

229-238

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-642-02812-0_27

Socpus ID

77951999012 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/77951999012

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