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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Suggested Citation:"Front Matter." National Research Council. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. Washington, DC: The National Academies Press. doi: 10.17226/1490.
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Quantitative Mocleling of Human Performance in Complex, Dynamic Systems Sheldon Baron, Dana S. Kruser, and Beverly Messick Huey, editors Panel on Human Performance Modeling Committee on Human Factors Commission on Behavioral and Social Sciences and Education National Research Council NATIONAL ACADEMY PRESS Washington, D.C. 1990

NationalAcademy Press · 2101 Constitution Avenue, N.W. . Washington, D.C. 20418 NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The members of the committee responsible for the report were chosen for their special competences and with regard to appropriate balance. This report has been reviewed by a group other than the authors according to procedures approved by a Report Review Committee consisting of members of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The National Academy of Sciences is a private, nonprofit, self-perpetuating society of dis- tinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare. Upon the authority of the charter granted to it lay the Congress in 1863, the Academy has a mandate that requires it to advise the federal government on scientific and technical matters. Dr. Frank Press is president of the National Academy of Sciences. The National Academy of Engineering was established in 1964, under the charter of the National Academy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in its administration and in the selection of its members, sharing with the blational Academy of Sciences the responsibility for advising the federal government. The National Academy of Engineering also sponsors engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achievements of engineers. Dr. Robert M. White is president of the National Academy of Engineering. The Institute of Medicine was established in 1970 by the National Academy of Sciences to secure the services of eminent members of appropriate professions in the examination of policy matters pertaining to the health of the public. She Institute acts under the responsibility given to the National Academy of Sciences by its congressional charter to be an adviser to the federal government and, upon its own initiative, to identity issues of medical care, research, and education. Dr. Samuel 0. Shier is president of the Institute of Medicine. The National Research Council was established By the National Academy of Sciences In 1916 to associate the broad community of science and technology with the Academy's purposes of furthering knowledge and advising the federal government. Functioning in accordance with general policies determined by the Academy, the Council has become the principal operating agency of both the National Academy of Sciences and the National Academy of Engineering in providing services to the government, the public, and the scientific and engineering communities. The Council is administered jointly by both Academies and the Institute of Medicine. Dr. Frank Press and Dr. Robert White are chairman and vice chairman, respectively, of the National Research Council. This work relates to Department of the Navy grant N0014-85-G-0093 issued By the Office of Naval Research under Contract Authority NR 19~}67. However, the content does not necessarily reflect the position or the policy of the government, and no official endorsement should be inferred. The United States Government has at least a royalty-free, nonexclusive, and irrevocable license throughout the world for government purposes to publish, translate, reproduce, deliver, perform, dispose of, and to authorize others so as to do, all or any portion of this work. Additional copies of this report are available from: National Academy Press 2101 Constitution Avenue, N.W Washington, DC 20418 S052 Printed in the United States of America Library of Congress Catalog Card No. 89~3540 International Standard Book Number 0-309-04135-X

PANEL ON HUMAN PERFORMANCE MODELING l SHELDON BARON (Chair), Computer and Information Sciences Division, BBM Laboratories, Inc., Cambridge, Massachusetts RENWICK E. CURRY, Tycho Inc., Palo Alto, California CHARLES P. GREENING, Human Factors Branch, Naval Weapons Center, China Lake, California (retired) EARL HUNT, Department of Psychology, University of Washington, Seattle CHARLES C. JORGENSEN, Engineering Physics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee NEVILLE P. MORAY, Department of Mechanical and Industnal Engineering, University of Illinois RICHARD W. PEW, Computer and Information Sciences Division, BEN Laboratories, Inc., Cambridge, Massachusetts WILLIAM B. ROUSE, Search Technology, Inc., Norcross, Georgia THOMAS B. SHERIDAN, Engineering and Applied Psychology, Massachusetts Institute of Technology ROBERT J. WHERRY, JR., Robert J. Wherry, Jr. Company, Chalfont, Pennsylvania HAROLD P. VAN COW, Study Director STANLEY DEUTSCH, Study Director, 198~1987 BEVERLY M. HUEY, Staff Officer DANA S. KRUSER, Consultant . . . 1H

COMMITTEE ON HUMAN FACTORS DOUGLAS H. HARRIS (Chair), Anacapa Sciences, Inc., Santa Barbara, California PAUL ~ ATIEWELL, Graduate School of Business Administration, New York University MOHAMED M. AYOUB, Institute of Biotechnology, Texas Tech University JEROME I. ELKIND, Systems Integration, Xerox Corporation, Sunnyvale, California (retired) MIRIAN M. GRADOICK, Human Resources, AT&T Corporation, Basking Ridge, New Jersey OSCAR GRUSKY, Department of Sociology, University of California, Los Angeles THOMAS K LANDAUER, Information Sciences Division, Bell Communications Research, Morristown, New Jersey NEVILLE P. MORAY, Department of Mechanical and Industrial Engineering, University of Illinois RAYMOND S. NICKERSON, BEN Laboratories, Inc., Cambridge, Massachusetts CHRISTOPHER I. WICKENS, Aviation Research Laboratory, University of Illinois, Savoy ROBERT C. WILLIGES, Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University J. FRANK YATES, Department of Psychology, University of Michigan 1V

Contents FOREWORD PREFACE . . . 1 INTRODUCTION.......................... Scope, 1 What Is Human Performance Modeling?, 2 Output Versus Process, 3 Predictive Versus Descriptive, 3 Prescriptive (Normative) Versus Descriptive, 4 p-Down Versus Bottom-Up, 4 Single-~sk (Limited Scope) Versus Multitask (Com- prehensive), 5 Modeling Methodology, 5 Why Use Human Performance Models?, 6 . . V11 Processes That May Benefit From Their Use, 6 Alternative (or Complementary) Methodologies to Modeling, 7 Benefits of Human Performance Modeling, 9 Genealogy of Human Performance Models, 10 2 APPROACHES TO HUMAN PERFORMANCE MODELING...16 Models of Limited Scope, 16 Larger, or Integrative, Approaches, 18 Information Processing, 20 Control Theory, 27 Ask Network, 34 Knowledge-Based, 42 Summary of Modeling Approaches, 50 v

3 APPLICATIONS .............................................. 50 Human Performance Models In Aircraft Operations, 53 Flight Control, 53 Aircrew Workload, 55 Air-to-Surface Search and Targeting, 58 Human Performance Models in Nuclear Power Operations, 59 Background, 59 Current Issues, 63 Summary, 64 Human Performance Models in Maintenance Operations, 64 Background, 64 Summary, 65 Human Performance Models in Supe~o~y Control, 67 Background, 67 Summary, 71 4 ISSUES AND RESEARCH RECOMMENDATIONS Overview, 72 Specifics, 74 Complex/Comprehensive Human Performance Models, 74 Model Parameterization, 76 Problems With Validation, 78 Underutilization/Inaccessibility of Human Performance Models, 80 Potential for Misuse or Misunderstanding, 82 Mental Models to Account for Mental Aspects of Frisks, 83 Developing and Using Knowledge-Based Models, 84 Accounting for Individual Differences, 85 Conclusion, 86 REFERENCES INDEX ........ V1 ..... 72 . . 87 ..95

Foreword The Committee on Human Factors was established in October 1980 by the Commission on Behavioral and Social Sciences and Education of the National Research Council. The committee is sponsored by the Office of Naval Research, the Air Force Office of Scientific Research, the Army Research Institute for the Behavioral and Social Sciences, the National Aeronautics and Space Administration, the National Science Foundation, the Air Force Armstrong Aerospace Medical Research Laboratory, the Army Advanced Systems Research Office, the Artay Human Engineering Laboratory, the Federal Aviation Administration, and the Nuclear Regula- tory Commission The principal objectives of the committee are to provide new perspectives on theoretical and methodological issues, to identity basic research needed to expand and strengthen the scientific basis of human fac- tors, and to attract scientists both inside and outside the field for interactive communication and performance of needed research. Human factors issues ame in every domain in which humans interact with the products of a technological society. To perform its role effec- t~vely, the committee draws on experts from a wide range of scientific and engineering disciplines. Members of the committee include specialists in such fields as psychology, engineering, biomechanics, physiology, medicine, cognitive sciences, machine intelligence, computer sciences, sociology, edu- cation, and human factors engineering. Other disciplines are represented in the working groups, workshops, and symposia organized by the committee. Each of these disciplines contributes to the basic data, theory, and methods required to improve the scientific basis of human factors. . . V11

A

Preface Human factors work in the systems development process involves both analytic and empirical studies of design alternatives. The use of human performance models (HPMs) to evaluate candidate designs has become increasingly important as the cost, personnel, and time required to perform full-scale simulation studies have increased. People are an essential part of human-machine systems, and it is substantially easier and less expensive to consider the impact of human capabilities and limitations on system operation and modify the system before it is built, than to modify it to conform to human limitations after it has been constructed. The development and use of human performance models have grown steadily since He successful application of servo-theory in the l950s to tracking and other manual control skills. However, a number of problems and unresolved issues have restricted the utility and application of HPMs in the design and development of systems. Many different approaches to modeling have been taken, and a wide varieW of limited models that focus on some particular aspect of human performance has been developed. The potential utilibr of these models would increase if an integrated representa- tion of human performance was developed that users and managers could easily understand and support. Most models that exist today are generally poorly understood except by those who have coninbuted to their development. Even seemingly simple models are fairly complex when examined in detail. A particular problem is understanding the rationale behind the assumptions, choice of parameters, and actual values that are incorporated into a model. A great deal of experience with a model is required to fully comprehend its sensitivity to parameter changes and its robustness in different applications. Because of the general lack of knowledge of the limitations and utility of various 1X

x PREFACE models, an incautious user may apply a model inappropriately, whereas a conservative user may avoid employing a model well suited to a particular need. Of equal concern is the problem of vending and validating models in the context of complex systems. This is compounded because new systems require that operators learn to use them, so a new system is essentially never available to experts to study. Inhere is evident need for guidance on ways to improve the utopia of existing models, to create more comprehensive models, and to validate them. Th meet this need, the Committee on Human Factors established the Panel on Human Performance Modeling. The focus of the worldng group was on HPMs that are specifically useful in the design and development of complex systems. The general purpose of the working group was to assess the capabilities and limitations of existing models, the conditions under which these models are useful, and the poss~bili~ of creating more comprehensive models of human behavior. It was beyond the scope of the panel to compare the solution of a problem with and without a model or to compare models with one another; however, alternative and complementary methodologies to modeling are discussed briefly. The primary goals of the panel were . approaches; to evaluate the strengths and weaknesses of alternative modeling to assess the conditions under which current models are of practical use; · to assess the potential for developing comprehensive models of human performance by integrating existing models c)r other alternative means; and · to recommend research or other courses of action necessary to improve HPMs. Chapter 1 of this report is introductory in nature and includes defi- nitions and characterizations of human performance modeling and a dis- cussion of its purposes. The chapter closes with a historical perspective on modeling approaches in the form of a genealogy of human performance models. In Chapter 2, the approaches deemed most relevant to the development of comprehensive human performance models are discussed. These include models of limited scope and their relation to comprehensive model devel- opment and use; an information processing approach; a control-theoretic approach; a task network approach; and a knowledge-based systems ap- proach. Brief descriptions of the approaches are provided along with their specific strengths and caveats on their use. A summarizing overview con- cludes the chapter by observing that a number of promising models for

PREFACE X1 complex human-machine interaction exist, but none are mature enough for general use. In Chapter 3, several applications of HPMs are discussed with a view to providing the reader with an indication of this scope as well as some of the problems In HEM use. Applications in the operation (control) of aircraft and nuclear power plants, in maintenance tasks, and in the monitoring and control of highly automated systems (supervisory control) are discussed. Chapter 4 concludes the report with a discussion of the views of the working group concerning the most important issues in developing comprehensive HPMs and recommendations for addressing them in terms of both use and needed research The panel, which met over a four-year period starting in December 1983, included 10 experts in the areas of mathematical psychology, cogni- tive psychology, experimental psychology, human factors, modern control theory, and artificial intelligence. Special thanks are extended to the mem- bers of this group for their unflagging cooperation and involvement in this project. I would also like to acknowledge the people who managed the me- chanics of transforming the products of the working group into this report. Thanks are due to Stanley Deutsch, former study director, who guided the project ~ the beginning; to Harold Van Cott, the current study director, for keeping the project on track; to Dana Kruser, project coordinator, for putting the materials submitted by the working group into first draft form and editing first drafts; and to Beverly Huey for editing the fina} drafts. I express my sincere gratitude to each of these individuals for their significant contn~utions. Sheldon Baron, Chair Panel on Human Performance Modeling

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This book describes and evaluates existing models of human performance and their use in the design and evaluation of new human-technology systems. Its primary focus is on the modeling of system operators who perform supervisory and manual control tasks. After an introduction on human performance modeling, the book describes information processing, control theory, task network, and knowledge-based models.

It explains models of human performance in aircraft operations, nuclear power plant control, maintenance, and the supervisory control of process control systems, such as oil refineries. The book concludes with a discussion of model parameterization and validation and recommends a number of lines of research needed to strengthen model development and application.

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