Human Performance Operating Picture for Shepherding a Swarm of Autonomous Vehicles

Raul Fernandez Rojas, Essam Debie, Justin Fidock, Michael Barlow, Kathryn Kasmarik, Sreenatha Anavatti, Matthew Garratt, Hussein A. Abbass

Research output: A Conference proceeding or a Chapter in BookChapterpeer-review


Due to many factors that range from ethical considerations and accountability to technological imperfection in autonomous systems, humans will continue to be an integral part of any meaningful autonomous system. While shepherding offers a technological concept that allows a human to operate a significantly larger number of autonomous systems that a human can handle in today’s environment, it is important to realise that a significant amount of accidents today are due to human error. The scalability promise that shepherding offers comes with possible challenges including those arising from the cognitive load imposed on human operators and the need to smoothly integrate the human, as a biological autonomous system, with the wider multi-agent autonomous system of future operating environments. In this chapter, we bring together the dimensions of this complex problem. We present carefully selected factors to cover human performance, especially for cognitively demanding tasks and situation awareness, and how these factors contribute to trust in the system. We then present the Human Factors Operating Picture (H-FOP), which offers a real-time situation awareness picture on human performance in this complex environment. We conclude with the concept of operation for integrating H-FOP with the human-swarm teaming problem, with a focus on the reliance of shepherding as the swarm guidance and control method.

Original languageEnglish
Title of host publicationShepherding UxVs for Human-Swarm Teaming
EditorsHussein A Abbass, Robert A Hunjet
Place of PublicationNetherlands
Number of pages31
ISBN (Electronic)9783030608989
ISBN (Print)9783030608972
Publication statusPublished - Mar 2021

Publication series

NameUnmanned System Technologies
ISSN (Print)2523-3734
ISSN (Electronic)2523-3742


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