The research reported in this thesis focuses on the decision making aspect of human-machine cooperation and reveals new insights from theoretical modeling to experimental evaluations: Two mathematical behavior models of two emancipated cooperation partners in a cooperative decision making process are introduced. The model-based automation designs are experimentally evaluated and thereby demonstrate their benefits compared to state-of-the-art approaches.
This book, on the ergonomics of human−machine systems, is aimed at engineers specializing in informatics, automation, production or robotics, who are faced with a significant dilemma during the conception of human−machine systems. On the one hand, the human operator guarantees the reliability of the system and has been known to salvage numerous critical situations through an ability to reason in unplanned, imprecise and uncertain situations; on the other hand, the human operator can be unpredictable and create disturbances in the automated system. The first part of the book is dedicated to the methods of human-centered design, from three different points of view, the various chapters focusing on models developed by human engineers and functional models to explain human behavior in their environment, models of cognitive psychology and models in the domain of automobile driving. Part 2 develops the methods of evaluation of the human−machine systems, looking at the evaluation of the activity of the human operator at work and human error analysis methods. Finally, Part 3 is dedicated to human−machine cooperation, where the authors show that a cooperative agent comprises a know-how and a so-called know-how-to-cooperate and show the way to design and evaluate that cooperation in real industrial contexts.
The present book includes a set of selected papers from the fourth “International Conference on Informatics in Control Automation and Robotics” (ICINCO 2007), held at the University of Angers, France, from 9 to 12 May 2007. The conference was organized in three simultaneous tracks: “Intelligent Control Systems and Optimization”, “Robotics and Automation” and “Systems Modeling, Signal Processing and Control”. The book is based on the same structure. ICINCO 2007 received 435 paper submissions, from more than 50 different countries in all continents. From these, after a blind review process, only 52 where accepted as full papers, of which 22 were selected for inclusion in this book, based on the classifications provided by the Program Committee. The selected papers reflect the interdisciplinary nature of the conference. The diversity of topics is an important feature of this conference, enabling an overall perception of several important scientific and technological trends. These high quality standards will be maintained and reinforced at ICINCO 2008, to be held in Funchal, Madeira - Portugal, and in future editions of this conference. Furthermore, ICINCO 2007 included 3 plenary keynote lectures given by Dimitar Filev (Ford Motor Company), Patrick Millot (Université de Valenciennes) and Mark W. Spong (University of Illinois at Urbana-Champaign).
Human-Machine Systems Design and Evaluation Methodology for Intelligent Vehicles examines the fields of designing and developing intelligent design and intelligent vehicle driving evaluation by using virtual reality, augmented reality, and other technologies. The book explains the methodologies and systems of interactive design, user evaluation and testing using virtual reality technology and augmented reality technology in intelligent cockpit design. With the rising prominence of electric vehicles and automatic driving (assisted) technology, intelligent vehicles are becoming a reality. Compared to traditional interactive design, artificial intelligence provides new opportunities and challenges for the interactive design of intelligent cockpit space, especially under the condition of intelligent assisted driving, the driver's behavior performance, multimodal interactive display interface design and evaluation. - Focuses on the interactive design methods of intelligent vehicles, as well as forward-looking design and testing methods of intelligent vehicle design - Emphasizes that interactive design should be carried out using the relevant elements of intelligent system in the design of intelligent cars: starting from the interactive characteristics of intelligence itself - Starts from AI interactive design and combines the field of cognitive science to develop the methods and technologies of vehicle borne equipment and collaborative human-computer interaction design - Includes design cases from the intelligent car interaction design laboratory of Tongji University and related scientific research projects in China.
The series of IFAC Symposia on Analysis, Design and Evaluation of Man-Machine Systems provides the ideal forum for leading researchers and practitioners who work in the field to discuss and evaluate the latest research and developments. This publication contains the papers presented at the 6th IFAC Symposium in the series which was held in Cambridge, Massachusetts, USA.
Decision-Making Techniques for Autonomous Vehicles provides a general overview of control and decision-making tools that could be used in autonomous vehicles. Motion prediction and planning tools are presented, along with the use of machine learning and adaptability to improve performance of algorithms in real scenarios. The book then examines how driver monitoring and behavior analysis are used produce comprehensive and predictable reactions in automated vehicles. The book ultimately covers regulatory and ethical issues to consider for implementing correct and robust decision-making. This book is for researchers as well as Masters and PhD students working with autonomous vehicles and decision algorithms. - Provides a complete overview of decision-making and control techniques for autonomous vehicles - Includes technical, physical, and mathematical explanations to provide knowledge for implementation of tools - Features machine learning to improve performance of decision-making algorithms - Shows how regulations and ethics influence the development and implementation of these algorithms in real scenarios
The Handbook of Human-Machine Interaction features 20 original chapters and a conclusion focusing on human-machine interaction (HMI) from analysis, design and evaluation perspectives. It offers a comprehensive range of principles, methods, techniques and tools to provide the reader with a clear knowledge of the current academic and industry practice and debate that define the field. The text considers physical, cognitive, social and emotional aspects and is illustrated by key application domains such as aerospace, automotive, medicine and defence. Above all, this volume is designed as a research guide that will both inform readers on the basics of human-machine interaction from academic and industrial perspectives and also provide a view ahead at the means through which human-centered designers, including engineers and human factors specialists, will attempt to design and develop human-machine systems.
This book includes papers presented at the ISDG12-GTM2019 International Meeting on Game Theory, as a joint meeting of the 12th International ISDG Workshop and the 13th "International Conference on Game Theory and Management”, held in St. Petersburg in July 2019. The topics cover a wide range of game-theoretic models and include both theory and applications, including applications to management.
This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science.
Aiming to outline the vision of realizing automated and intelligent communication networks in the era of intelligence, this book describes the development history, application scenarios, theories, architectures, and key technologies of Huawei's Autonomous Driving Network (ADN) solution. In the book, the authors explain the design of the top-level architecture, hierarchical architecture (ANE, NetGraph, and AI Native NE), and key feature architecture (distributed AI and endogenous security) that underpin Huawei's ADN solution. The book delves into various key technologies, including trustworthy AI, distributed AI, digital twin, network simulation, digitization of knowledge and expertise, human-machine symbiosis, NE endogenous intelligence, and endogenous security. It also provides an overview of the standards and level evaluation methods defined by industry and standards organizations, and uses Huawei's ADN solution as an example to illustrate how to implement AN. This book is an essential reference for professionals and researchers who want to gain a deeper understanding of automated and intelligent communication networks and their applications.