Literature DB >> 28146676

From Here to Autonomy.

Mica R Endsley1.   

Abstract

As autonomous and semiautonomous systems are developed for automotive, aviation, cyber, robotics and other applications, the ability of human operators to effectively oversee and interact with them when needed poses a significant challenge. An automation conundrum exists in which as more autonomy is added to a system, and its reliability and robustness increase, the lower the situation awareness of human operators and the less likely that they will be able to take over manual control when needed. The human-autonomy systems oversight model integrates several decades of relevant autonomy research on operator situation awareness, out-of-the-loop performance problems, monitoring, and trust, which are all major challenges underlying the automation conundrum. Key design interventions for improving human performance in interacting with autonomous systems are integrated in the model, including human-automation interface features and central automation interaction paradigms comprising levels of automation, adaptive automation, and granularity of control approaches. Recommendations for the design of human-autonomy interfaces are presented and directions for future research discussed.

Entities:  

Keywords:  adaptive automation; autonomy; human–automation interaction; level of automation; monitoring; situation awareness; trust; vigilance

Mesh:

Year:  2016        PMID: 28146676     DOI: 10.1177/0018720816681350

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  9 in total

1.  Human Cooperation When Acting Through Autonomous Machines.

Authors:  Celso M de Melo; Stacy Marsella; Jonathan Gratch
Journal:  Proc Natl Acad Sci U S A       Date:  2019-02-11       Impact factor: 11.205

Review 2.  The human factors of mineworker fatigue: An overview on prevalence, mitigation, and what's next.

Authors:  Timothy J Bauerle; John J Sammarco; Zoë J Dugdale; Drew Dawson
Journal:  Am J Ind Med       Date:  2021-10-20       Impact factor: 3.079

Review 3.  Human-Autonomy Teaming: A Review and Analysis of the Empirical Literature.

Authors:  Thomas O'Neill; Nathan McNeese; Amy Barron; Beau Schelble
Journal:  Hum Factors       Date:  2020-10-22       Impact factor: 3.598

4.  Feedback and Direction Sources Influence Navigation Decision Making on Experienced Routes.

Authors:  Yu Li; Weijia Li; Yingying Yang; Qi Wang
Journal:  Front Psychol       Date:  2019-09-13

5.  High-Level Teleoperation System for Aerial Exploration of Indoor Environments.

Authors:  Werner Alexander Isop; Christoph Gebhardt; Tobias Nägeli; Friedrich Fraundorfer; Otmar Hilliges; Dieter Schmalstieg
Journal:  Front Robot AI       Date:  2019-10-23

Review 6.  Updating our understanding of situation awareness in relation to remote operators of autonomous vehicles.

Authors:  Clare Mutzenich; Szonya Durant; Shaun Helman; Polly Dalton
Journal:  Cogn Res Princ Implic       Date:  2021-02-19

7.  Characterization of Indicators for Adaptive Human-Swarm Teaming.

Authors:  Aya Hussein; Leo Ghignone; Tung Nguyen; Nima Salimi; Hung Nguyen; Min Wang; Hussein A Abbass
Journal:  Front Robot AI       Date:  2022-02-17

8.  Distributed cognition for collaboration between human drivers and self-driving cars.

Authors:  Alice Plebe; Gastone Pietro Rosati Papini; Antonello Cherubini; Mauro Da Lio
Journal:  Front Artif Intell       Date:  2022-08-25

9.  Drivers of partially automated vehicles are blamed for crashes that they cannot reasonably avoid.

Authors:  Niek Beckers; Luciano Cavalcante Siebert; Merijn Bruijnes; Catholijn Jonker; David Abbink
Journal:  Sci Rep       Date:  2022-09-28       Impact factor: 4.996

  9 in total

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