Human Performance In Automated And Autonomous Systems Two Volume Set

This book examines recent advances in theories, models, and methods relevant to automated and autonomous systems. The following chapters provide perspectives on modern autonomous systems, such as self-driving cars and unmanned aerial systems, directly from the professionals working with and studying them. Current theories surrounding topics such as vigilance, trust, and fatigue are examined throughout as predictors of human performance in the operation of automated systems. The challenges related to attention and effort in autonomous vehicles described within give credence to still-developing methods of training and selecting operators of such unmanned systems. The book further recognizes the need for human-centered approaches to design; a carefully crafted automated technology that places the "human user" in the center of that design process. Features Combines scientific theories with real-world applications where automated technologies are implemented Disseminates new understanding as to how automation is now transitioning to autonomy Highlights the role of individual and team characteristics in the piloting of unmanned systems and how models of human performance are applied in system design Discusses methods for selecting and training individuals to succeed in an age of increasingly complex human-machine systems Provides explicit benchmark comparisons of progress across the last few decades, and identifies future prognostications and the constraints that impinge upon these lines of progress Human Performance in Automated and Autonomous Systems: Current Theory and Methods illustrates the modern scientific theories and methods to be applied in real-world automated technologies.

This two-volume set addresses a variety of human factors issues and engineering concerns across various real-world applications such as aviation and driving, cybersecurity, and healthcare systems. The contents of these books also present recent theories and methods related to human performance, workload and usability assessment in automated and autonomous systems. In this set, the authors discuss both current and developing topics of advanced automation technologies and present emerging practical challenges. Topics covered include unmanned aerial systems and self-driving cars, individual and team performance, human-robot interaction, and operator selection and training. Both practical and theoretical discussions of modern automated and autonomous systems are provided throughout each of the volumes. These books are suitable for those first approaching the issues to those well versed in these fast-moving areas, including students, teachers, researchers, engineers, and policy makers alike. Volume 1 - Human Performance in Automated and Autonomous Systems: Current Theory and Methods Volume 2 - Human Performance in Automated and Autonomous Systems: Emerging Issues and Practical Perspectives

This book is devoted to the examination of emerging practical issues related to automated and autonomous systems. The book highlights the significance of these emergent technologies that determine the course of our daily lives. Each unique chapter highlights human factors and engineering concerns across real-world applications, including matters related to aviation and healthcare, human-robot interaction, transportation systems, cybersecurity and cyber defense. This book also depicts the boundaries that separate humans from machine as we continue to become ever more immersed in and symbiotic with these fast-emerging technologies. Automation, across many occupations, has transitioned the human to a role of monitoring machines, presenting challenges related to vigilance and workload. This book identifies the importance of an approach to automated technology that emphasizes the "human user" at the center of the design process. Features Provides perspectives on the role of the individual and teams in complex technical systems such as aviation, healthcare, and medicine Presents the development of highly autonomous systems related to human safety and performance Examines solutions to human factors challenges presented by modern threats to data privacy and cybersecurity Discusses human perceptual and cognitive capabilities underwriting to the design of automated and autonomous systems • Provides in-depth, expert reviews of context-related developments in automation and human-robot teaming Human Performance in Automated and Autonomous Systems: Emerging Issues and Practical Perspectives applies scientific theory directly to real-world systems where automation and autonomous technology is implemented.

The third edition of Human Factors in Aviation and Aerospace is a fully updated and expanded version of the highly successful second edition. Written for the widespread aviation community including students, engineers, scientists, pilots, managers, government personnel, etc., this edition continues to offer a comprehensive overview, including pilot performance, human factors in aircraft design, and vehicles and systems. With new editors, this edition adds chapters on aviator attention and perception, accident investigations, automated systems in civil transport airplanes, and aerospace. Multicontributed by leading professionals in the field, this book is the ultimate resource for anyone in the aviation and aerospace industries. Uses real-world case examples of dangers and solutions Includes a new chapter on spaceflight human factors and decision making Examines future directions for automated systems, in two new, separate chapters

Human Factors in Simulation and Training: Theory and Methods covers theoretical concepts on human factors principles as they apply to the fields of simulation and training in the real world. This book discusses traditional and nontraditional aspects of simulation and training. Topics covered include simulation fidelity, transfer of training, limits of simulation and training, virtual reality in the training environment, simulation-based situation awareness training, automated performance measures, performance assessment in simulation, adaptive simulation-based training, and scoring simulations with artificial intelligence This book will be a valuable resource for professionals and graduate students in the fields of ergonomics, human factors, computer engineering, aerospace engineering and occupational health and safety.

"There is perhaps no facet of modern society where the influence of computer automation has not been felt. Flight management systems for pilots, diagnostic and surgical aids for physicians, navigational displays for drivers, and decision-aiding systems for air-traffic controllers, represent only a few of the numerous domains in which powerful new automation technologies have been introduced. The benefits that have been reaped from this technological revolution have been many. At the same time, automation has not always worked as planned by designers, and many problems have arisen--from minor inefficiencies of operation to large-scale, catastrophic accidents. Understanding how humans interact with automation is vital for the successful design of new automated systems that are both safe and efficient. The influence of automation technology on human performance has often been investigated in a fragmentary, isolated manner, with investigators conducting disconnected studies in different domains. There has been little contact between these endeavors, although principles gleaned from one domain may have implications for another. Also, with a few exceptions, the research has tended to be empirical and only theory-driven. In recent years, however, various groups of investigators have begun to examine human performance in automated systems in general and to develop theories of human interaction with automation technology. This book presents the current theories and assesses the impact of automation on different aspects of human performance. Both basic and applied research is presented to highlight the general principles of human-computer interaction in several domains where automation technologies are widely implemented. The major premise is that a broad-based, theory-driven approach will have significant implications for the effective design of both current and future automation technologies. This volume will be of considerable value to researchers in human"--Provided by publisher.

This volume explores the intersection of robust intelligence (RI) and trust in autonomous systems across multiple contexts among autonomous hybrid systems, where hybrids are arbitrary combinations of humans, machines and robots. To better understand the relationships between artificial intelligence (AI) and RI in a way that promotes trust between autonomous systems and human users, this book explores the underlying theory, mathematics, computational models, and field applications. It uniquely unifies the fields of RI and trust and frames it in a broader context, namely the effective integration of human-autonomous systems. A description of the current state of the art in RI and trust introduces the research work in this area. With this foundation, the chapters further elaborate on key research areas and gaps that are at the heart of effective human-systems integration, including workload management, human computer interfaces, team integration and performance, advanced analytics, behavior modeling, training, and, lastly, test and evaluation. Written by international leading researchers from across the field of autonomous systems research, Robust Intelligence and Trust in Autonomous Systems dedicates itself to thoroughly examining the challenges and trends of systems that exhibit RI, the fundamental implications of RI in developing trusted relationships with present and future autonomous systems, and the effective human systems integration that must result for trust to be sustained. Contributing authors: David W. Aha, Jenny Burke, Joseph Coyne, M.L. Cummings, Munjal Desai, Michael Drinkwater, Jill L. Drury, Michael W. Floyd, Fei Gao, Vladimir Gontar, Ayanna M. Howard, Mo Jamshidi, W.F. Lawless, Kapil Madathil, Ranjeev Mittu, Arezou Moussavi, Gari Palmer, Paul Robinette, Behzad Sadrfaridpour, Hamed Saeidi, Kristin E. Schaefer, Anne Selwyn, Ciara Sibley, Donald A. Sofge, Erin Solovey, Aaron Steinfeld, Barney Tannahill, Gavin Taylor, Alan R. Wagner, Yue Wang, Holly A. Yanco, Dan Zwillinger.

This book explores how Artificial Intelligence (AI), by leading to an increase in the autonomy of machines and robots, is offering opportunities for an expanded but uncertain impact on society by humans, machines, and robots. To help readers better understand the relationships between AI, autonomy, humans and machines that will help society reduce human errors in the use of advanced technologies (e.g., airplanes, trains, cars), this edited volume presents a wide selection of the underlying theories, computational models, experimental methods, and field applications. While other literature deals with these topics individually, this book unifies the fields of autonomy and AI, framing them in the broader context of effective integration for human-autonomous machine and robotic systems. The contributions, written by world-class researchers and scientists, elaborate on key research topics at the heart of effective human-machine-robot-systems integration. These topics include, for example, computational support for intelligence analyses; the challenge of verifying today’s and future autonomous systems; comparisons between today’s machines and autism; implications of human information interaction on artificial intelligence and errors; systems that reason; the autonomy of machines, robots, buildings; and hybrid teams, where hybrid reflects arbitrary combinations of humans, machines and robots. The contributors span the field of autonomous systems research, ranging from industry and academia to government. Given the broad diversity of the research in this book, the editors strove to thoroughly examine the challenges and trends of systems that implement and exhibit AI; the social implications of present and future systems made autonomous with AI; systems with AI seeking to develop trusted relationships among humans, machines, and robots; and the effective human systems integration that must result for trust in these new systems and their applications to increase and to be sustained.