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Data Science and Simulation in Transportation Research

Book Description

Given its effective techniques and theories from various sources and fields, data science is playing a vital role in transportation research and the consequences of the inevitable switch to electronic vehicles. This fundamental insight provides a step towards the solution of this important challenge. Data Science and Simulation in Transportation Research highlights entirely new and detailed spatial-temporal micro-simulation methodologies for human mobility and the emerging dynamics of our society. Bringing together novel ideas grounded in big data from various data mining and transportation science sources, this book is an essential tool for professionals, students, and researchers in the fields of transportation research and data mining.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
  5. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
  6. Foreword
  7. Preface
  8. Acknowledgment
  9. Chapter 1: Mobility Profiling
    1. ABSTRACT
    2. INTRODUCTION
    3. THE BIG DATA CHALLENGE IN MOBILITY: GPS AND GSM DATA
    4. INDIVIDUAL MOBILITY PROFILING
    5. CASE OF STUDY I: DISTRIBUTED COMPUTATION APPLICATION
    6. CASE OF STUDY II: CAR POOLING APPLICATION
    7. DISCOVERY CALL BEHAVIORS
    8. REAL CASE OF STUDY III: DISCOVERING CALL BEHAVIORS IN PISA
    9. CONCLUSION
  10. Chapter 2: On Predicting the Future Locations of Moving Objects
    1. ABSTRACT
    2. INTRODUCTION
    3. APPLICATIONS
    4. WHERENEXT
    5. IMPROVING WHERENEXT
    6. CONCLUSION
  11. Chapter 3: Synthetic Population Techniques in Activity-Based Research
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED RESEARCH
    4. WORKING PROCEDURE AND EMPIRICAL CASE
    5. ISSUES AND PROPOSED SOLUTIONS
    6. CONCLUSION
    7. APPENDIX
  12. Chapter 4: Issues in Feathers Application in the Seoul Metropolitan Area
    1. ABSTRACT
    2. INTRODUCTION
    3. STUDY AREA
    4. TRAVEL DEMAND RESEARCH IN KOREA
    5. FEATHERS
    6. ISSEUS IN SEOUL ABM
    7. CONCLUSION
  13. Chapter 5: The Application of an Integrated Behavioral Activity-Travel Simulation Model for Pricing Policy Analysis
    1. ABSTRACT
    2. INTRODUCTION
    3. INTEGRATED DEMAND-SUPPLY MODELING FRAMEWORK
    4. ENHANCEMENT OF MODELING FRAMEWORK TO REFLECT PRICING IMPACTS
    5. CASE STUDY DEMONSTRATION
    6. RESULTS OF MODEL APPLICATION
    7. CONCLUSION AND DISCUSSION
  14. Chapter 6: An Effective Methodology for Road Accident Data Collection in Developing Countries
    1. ABSTRACT
    2. INTRODUCTION
    3. ACCIDENT DATA COLLECTION MECHANISM IN DEVELOPING NATIONS
    4. NGO BASED DATA COLLECTION - KARACHI CASE STUDY
    5. SUCCESS STORIES
    6. CONCLUSION
  15. Chapter 7: Traffic Safety Implications of Travel Demand Management Policies
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. METHODOLOGY
    5. VALIDATION AND SENSITIVITY ANALYSIS
    6. RESULTS
    7. CONCLUSION AND DISCUSSION
  16. Chapter 8: Evaluation of Spatio-Temporal Microsimulation Systems
    1. ABSTRACT
    2. INTRODUCTION
    3. PROPERTIES OF MOBILITY DATA
    4. DATA INPUT AND EXTERNAL MODEL VALIDATION
    5. INTERNAL MODEL VALIDATION
    6. VALIDATION USE CASES
    7. EVALUATING GPS AND GSM DATA IN THE REGION OF PISA
    8. CONCLUSION
  17. Chapter 9: Activity-Based Travel Demand Forecasting Using Micro-Simulation
    1. ABSTRACT
    2. INTRODUCTION
    3. FEATHERS FRAMEWORK FOR FLANDERS
    4. METHODOLOGY
    5. RESULTS AND DISCUSSION
    6. CONCLUSION
  18. Chapter 10: A Driver’s Mind
    1. ABSTRACT
    2. INTRODUCTION
    3. A BIT OF HISTORY
    4. HUMAN DRIVER BEHAVIOUR – A STATE OF THE ART
    5. CONCLUSION
  19. Chapter 11: Large-Scale Agent-Based Models for Transportation Network Management under Unplanned Events
    1. ABSTRACT
    2. INTRODUCTION
    3. AGENT-BASED MODELING IN TRANSPORTATION
    4. THE BUFFALO-NIAGARA TRANSIMS MODEL
    5. CALIBRATING THE MODEL FOR INCELEMENT WEATHER EVENTS
    6. MODEL APPLICATIONS
    7. CONCLUSION
  20. Chapter 12: Agent-Based Modeling for Carpooling
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND – LITERATURE OVERVIEW
    4. CO-TRAVELING SERVICES CONTEXT
    5. COOPERATION BY CARPOOLING
    6. AGENT-BASED MODEL TO EXERCISE ADVISOR SOFTWARE
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
  21. Chapter 13: The Evolution from Electric Grid to Smart Grid
    1. ABSTRACT
    2. INTRODUCTION TO ELECTRICAL POWER SYSTEMS
    3. COMPONENTS OF THE ELECTRICAL POWER SYSTEM
    4. POWER SYSTEM CONTROL
    5. FUNDAMENTALS OF ELECTRICITY MARKETS
    6. THE FUTURE POWER SYSTEMS
  22. Chapter 14: Adding Electric Vehicle Modeling Capability to an Agent-Based Transport Simulation
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PRECEDING WORK
    5. THE TRANSPORTATION ENERGY SIMULATION FRAMEWORK
    6. MATSIM
    7. TES INTEGRATION WITH MATSIM
    8. MODULES
    9. CASE STUDY: CITY OF ZURICH
    10. FLEET DYNAMICS
    11. ENERGY CONSUMPTION MODEL
    12. TRAVEL DEMAND AND TRAFFIC SIMULATION MODEL
    13. POWER SYSTEM SIMULATION AND LOAD BALANCING
    14. SCENARIO OVERVIEW
    15. TES INTEGRATION AND SIMULATIONS
    16. RESULTS – ENERGY AND EMISSIONS
    17. RESULTS – DISTRIBUTION NETWORK
    18. DISCUSSION
    19. FUTURE WORK
    20. CONCLUSION
  23. Chapter 15: Impacts of Electric Mobility on the Electric Grid
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. ADOPTED SOLUTION
    5. TECHNICAL RESULTS
    6. CONCLUSION AND FUTURE WORK
  24. Chapter 16: Electric Vehicles in the Smart Grid
    1. ABSTRACT
    2. INTRODUCTION
    3. SETTING THE SCENE
    4. PRINCIPLES OF THE COORDINATION ALGORITHMS
    5. ACTIVITY BASED MODELS AND SPATIO-TEMPORAL POWER REQUIREMENT
    6. SIMULATION RESULTS
    7. DISCUSSION
    8. CONCLUSION
    9. EPILOGUE
  25. Chapter 17: Grid and Fleet Impact Mapping of EV Charge Opportunities
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. FLEET MODELING
    5. ASSUMPTIONS
    6. RESULTS
    7. CONCLUSION
  26. Compilation of References
  27. About the Contributors