UNIVERSITY OF CALIFORNIA, IRVINE Paradigms of Identifying and Quantifying Uncertainty and Information in Constructing a Cognition-Modeling Framework of Human-Machine Transportation Systems DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Civil Engineering by Jiangbo Gabriel Yu Dissertation Committee: Professor R. Jayakrishnan, Chair Professor Jean-Daniel Saphores Associate Professor Prof. Wenlong Jin 2018 Portion of Chapter 2 © 2018 IEEE Portion of Chapter 5 © 2017 Transportation Research Board Rest of the dissertation © 2018 Jiangbo Gabriel Yu DEDICATION To my parents and mentors in recognition of their guidance ii CONTENTS LIST OF FIGURES ………………………………..……………………………………………………………………………….. vi LIST OF TABLES ……………………………………………..……………………………………………………………….…… ix ACKNOWLEDGMENTS ......…….…………………………….....…………………………………………………………….... x CURRICULUM VITAE ..……………………………………………..………………………………………………….……….. xi ABSTRACT OF THE DISSERTATION …………………………………..………………………................................. xii CHAPTER 1 INTRODUCTION .............................................................................................................................. 1 CHAPTER 2 A COGNITION-BASED MODELING AND ANALYTICAL FRAMEWORK ............................ 5 Motivations .............................................................................................................................................. 5 Literature Review .................................................................................................................................... 8 Framework ............................................................................................................................................ 13 Physical Interaction ........................................................................................................................... 15 Space of Observables ......................................................................................................................... 15 Cognition ............................................................................................................................................ 16 Analytical Examples .............................................................................................................................. 20 Human Driving Behavior .................................................................................................................. 20 Multi-stakeholder planning decision ............................................................................................... 21 Numerical Feasibility Study – Human-ACV Mixed Flows ................................................................... 22 Background ........................................................................................................................................ 23 Defining Agent Class .......................................................................................................................... 23 Defining PISOO Class ......................................................................................................................... 27 Agent Instantiation and Simulation ................................................................................................. 28 Density, Market Penetration, and Risk Preference Sensitivity Test .............................................. 30 Highlighted Features ......................................................................................................................... 34 Feasibility and Advantage ................................................................................................................. 36 Computational Efficiency .................................................................................................................. 37 Conclusion .............................................................................................................................................. 39 CHAPTER 3 QUANTIFYING INFORMATION AS CHANGE OF PERCEIVED UNCERTAINTY ........... 41 Background and Literature Review ..................................................................................................... 41 Methodology .......................................................................................................................................... 44 Numerical Example ............................................................................................................................... 48 Conclusion .............................................................................................................................................. 58 CHAPTER 4 ELASTIC SURPRISE THEORY FOR DECISION UNDER RISK ............................................ 60 iii Introduction ........................................................................................................................................... 60 Literature Review .................................................................................................................................. 62 More on Scale and Convexity Paradox in Existing Methods .............................................................. 64 Elastic Surprise (ES) .............................................................................................................................. 65 Logarithmic ES Function and Information Entropy ........................................................................... 68 Properties and Cognitive Implication .................................................................................................. 72 Limit at ퟎ + ........................................................................................................................................ 72 Rationality, Stochastic Dominance, and Trade-off Consistency .................................................... 74 EUT and Its Revision ............................................................................................................................. 75 Reference Dependency and Relationship with CPT ........................................................................... 77 Three Perspectives ................................................................................................................................ 81 ES in Mean-Variance (MV) Method ...................................................................................................... 82 Empirical Study on Route Choice under Risk...................................................................................... 83 Conclusion .............................................................................................................................................. 87 CHAPTER 5 MULTICLASS, MULTICRITERIA DYNAMIC TRAFFIC ASSIGNMENT WITH PATH- DEPENDENT LINK COST AND ENTROPY-BASED RISK PREFERENCE ................................................ 89 Introduction ........................................................................................................................................... 89 Literature Review .................................................................................................................................. 91 Important Concepts............................................................................................................................... 93 Path-dependent Link Cost ................................................................................................................ 93 Uncertainty, Reliability, Risk, and Variability ................................................................................. 94 Entropy-based Measure of Perceived Uncertainty ............................................................................. 95 Single-Class Single-Criterion DUE Formulation .................................................................................. 99 Multi-Class Multi-Criteria Extension With Path-Dependent Link Cost ........................................... 102 Stochastic Gradient Project Based Solution ...................................................................................... 103 Case Study ............................................................................................................................................ 105 Results Discussion ............................................................................................................................... 110 Conclusion and Future Direction ....................................................................................................... 114 CHAPTER 6 CONCLUSION ............................................................................................................................... 116 APPENDICES ....................................................................................................................................................... 121 Appendix A ........................................................................................................................................... 121 Appendix B ........................................................................................................................................... 122 Appendix C ........................................................................................................................................... 122 iv REFERENCES ......................................................................................................................................................