Patrick Millot has been Full Professor at the University of Valenciennes in France since 1989. He conducts research on Automation Sciences, Artificial Intelligence and Human-Machine Systems (HMS). He is the author of approximately 200 publications and collective books. He has led several regional, national and international projects on supervisory control and transport safety.

• FOREWORD xiBernard DUBUISSONINTRODUCTION xvPatrick MILLOTPART 1. DESIGN OF HUMAN–MACHINE SYSTEMS 1CHAPTER 1. HUMAN-CENTERED DESIGN 3Patrick MILLOT1.1. Introduction 31.2. The task–system–operator triangle 41.2.1. Controlling the diversity of the tasks depending on the situation 41.2.2. Managing the complexity of the system 91.2.3. Managing human complexity 101.3. Organization of the human–machine system 211.3.1. The ambiguous role of the operator in automated systems 211.3.2. Allocating humans with their proper role 231.3.3. Sharing tasks and functions between humans and machines 241.4. Human-centered design methodology 331.5. Conclusion 351.6. Bibliography 36CHAPTER 2. INTEGRATION OF ERGONOMICS IN THE DESIGN OF HUMAN–MACHINE SYSTEMS 43Christine CHAUVIN and Jean-Michel HOC2.1. Introduction 432.2. Classic and partial approaches of the system 462.2.1. Machine-centered approach 462.2.2. Activity and human-based approaches 492.3. The central notion of performance (Long, Dowell and Timmer) 522.4. An integrated approach: cognitive work analysis 592.4.1. Domain analysis 602.4.2. Task analysis 682.4.3. Analysis of information-processing strategies 712.4.4. Socio-organizational approach 732.4.5. Analysis of competences 762.4.6. Some general remarks on the integrated approach 782.5. Conclusion 792.6. Bibliography 81CHAPTER 3. THE USE OF ACCIDENTS IN DESIGN: THE CASE OF ROAD ACCIDENTS 87Gilles MALATERRE, Hélène FONTAINE and Marine MILLOT3.1. Accidents, correction and prevention 873.2. Analysis of accidents specific to the road 893.2.1. Road accidents as a statistical unit 893.2.2. Accidents as diagnosis tools 913.3. Need-driven approach 933.3.1. Definition of needs from the analysis of accidents 933.3.2. Particular case of urban areas 963.4. A priori analyses 983.5. What assistance for which needs? 1013.5.1. Collision with a stationary vehicle 1023.5.2. The struck vehicle is waiting to turn on an NR or a DR 1033.5.3. Catching up with a slower vehicle 1033.5.4. Dense lines: major incident at the front 1053.5.5. Dense line: violent accident happening just in front 1063.5.6. Dense line: sudden slowing 1063.6. Case of cooperative systems 1073.7. Using results in design 1083.7.1. Detection of a slower user 1103.7.2. Detection of several stopped vehicles blocking all the lanes 1103.7.3. Detection of a stopped vehicle completely or partially obstructing a road 1113.7.4. Detection of a vehicle preparing to turn left 1113.7.5. Detection of light two-wheelers circulating on the right-hand side of the road 1123.7.6. Detection of a disturbance at the front of the line 1123.7.7. Prevention of wild insertions 1133.7.8. Prevention of frontal collisions 1133.8. Conclusion 1133.9. Bibliography 114PART 2. EVALUATION MODELS OF HUMAN–MACHINE SYSTEMS 119CHAPTER 4. MODELS BASED ON THE ANALYSIS OF HUMAN BEHAVIOR: EXAMPLE OF THE DETECTION OF HYPO-VIGILANCE IN AUTOMOBILE DRIVING 121Jean-Christophe POPIEUL, Pierre LOSLEVER and Philippe SIMON4.1. Introduction 1214.2. The different models used in detection and diagnosis 1224.2.1. Methods based on knowledge models 1224.2.2. Classification methods: pattern recognition 1254.3. The case of human–machine systems 1354.4. Example of application: automobile driving 1384.4.1. Automobile driving 1384.4.2. Difficulties with diagnosing losses in vigilance 1414.4.3. Approach applied 1434.5. Conclusion 1624.6. Bibliography 165CHAPTER 5. EVALUATION OF HUMAN RELIABILITY IN SYSTEMS ENGINEERING 171Frédéric VANDERHAEGEN, Peter WIERINGA and Pietro Carlo CACCIABUE5.1. Introduction 1715.2. Principles of evaluating human reliability 1735.2.1. Human reliability versus human error 1735.2.2. General approach for the analysis of human reliability 1745.2.3. Synthetic review of methods 1765.2.4. Discussion 1785.3. Analysis of dynamic reliability 1805.3.1. The DYLAM method 1805.3.2. The HITLINE method 1835.4. Analysis of altered or added tasks 1875.4.1. Principles of the ACIH method 1875.4.2. Acceptability and evaluation of human behaviors 1885.4.3. Example of application 1915.5. Perspectives for the design of a safe system 1945.6. Conclusion 1975.7. Bibliography 198PART 3. HUMAN–MACHINE COOPERATION 205CHAPTER 6. CAUSAL REASONING: A TOOL FOR HUMAN–MACHINE COOPERATION 207Jacky MONTMAIN6.1. Introduction 2076.2. Supervision 2086.3. Qualitative model 2146.3.1. The origins 2146.3.2. Current models 2166.3.3. The evolution of qualitative reasoning (QR) 2176.4. Causal graphs and event-based simulation 2206.4.1. The causal graph 2226.4.2. Evolution and event 2246.4.3. Simulation 2276.5. Hierarchy of behavior models 2356.5.1. Definition of a graph hierarchy 2366.5.2. Creation of the hierarchy 2376.5.3. Online construction of graphs 2386.6. Fault filtering 2426.6.1. Causality and digital simulators 2426.6.2. Generation of residuals and causal structure 2476.6.3. Interpretation of the errors for the isolation and filtering of faults 2486.6.4. Advantages for supervision 2526.7. Discussion and conclusion 2566.8. Bibliography 261CHAPTER 7. HUMAN–MACHINE COOPERATION: A FUNCTIONAL APPROACH 273Jean-Michel HOC7.1. Introduction 2737.2. A functional approach to cooperation 2757.3. Cooperation in actions 2787.4. Cooperation in planning 2807.5. Meta-cooperation 2817.6. Conclusion 2827.7. Bibliography 283CHAPTER 8. THE COMMON WORK SPACE FOR THE SUPPORT OF SUPERVISION AND HUMAN–MACHINE COOPERATION 285Serge DEBERNARD, Bernard RIERA and Thierry POULAIN8.1. Introduction 2858.2. Human–machine cooperation 2878.2.1. Definitions of human–machine cooperation 2878.2.2. Characterization of cooperation activities 2898.2.3. Common work space: human–machine cooperation medium 2928.3. Application in air traffic control 2948.3.1. Dynamic allocation of tasks 2958.3.2. Air traffic control 2968.3.3. First studies: SPECTRA projects 2978.3.4. The AMANDA project 3038.4. Application to the process of nuclear combustibles reprocessing 3058.4.1. Introduction 3058.4.2. Human supervision tasks 3078.4.3. Design methodology of supervision systems adapted to humans 3108.4.4. Improvement of the supervision and diagnosis system 3118.4.5. Approximate reasoning 3138.4.6. The use of cognitive principles in the design of supervision tools 3178.4.7. An example of an advanced supervision system (ASS) 3238.5. Conclusion 3328.6. Acronyms 3338.7. Bibliography 334CHAPTER 9. HUMAN–MACHINE COOPERATION AND SITUATION AWARENESS 343Patrick MILLOT and Marie-Pierre PACAUX-LEMOINE9.1. Introduction 3439.2. Collective situation awareness 3449.3. Structural approaches of human–machine cooperation 3469.3.1. Dynamic allocation of tasks: horizontal cooperation structure 3479.3.2. Vertical structure for cooperation 3489.3.3. Multilevel structure for the dynamic allocation of tasks 3519.4. Human–machine cooperation: a functional approach 3539.4.1. Cooperative agents, forms of cooperation 3539.4.2. Organization and cooperation 3569.4.3. Human factors activating or inhibiting cooperation 3589.4.4. Multilevel cooperative organization 3599.4.5. Common work space (CWS) 3609.5. Common work space for team-SA 3679.6. Conclusion 3699.7. Bibliography 370CONCLUSION 375Patrick MILLOTLIST OF AUTHORS 379INDEX 381