Smart Urban Mobility: Transport Planning in the Age of Big Data and Digital Twins explores the data-driven paradigm shift in urban mobility planning and examines how well-established practices and strong data analytics efforts can be better aligned to fit transport planning practices and "smart" mobility management needs. The book provides a comprehensive survey of the major big data and technology resources derived from smart cities research which are collectively poised to transform urban mobility. Chapters highlight the important aspects of each data source affecting applicability, along with the outcomes of smart mobility measures and campaigns.Transport planners, urban policymakers, public administrators, city managers, data scientists, and consulting companies managing smart city interventions and data-driven urban transformation projects will gain a better understanding of this up-and-coming research from this book’s detailed overview and numerous practical examples and best practices for operational deployment.
1. Chapter 1 Introduction - p. 1 2. Chapter 2 Introduction to smart mobility - p. 9 3. Chapter 3 The new challenge of smart urban mobility - p. 25 4. Chapter 4 Small and big data for mobility studies - p. 79 5. Chapter 5 Data analytics - p. 121 6. 5.1: Objectives of the chapter - p. 121 7. 5.2: Word cloud - p. 121 8. 5.3: Data analytics introduction - p. 121 9. 5.4: Data analytics workflow - p. 122 10. 5.5: Machine learning - p. 134 11. 5.6: Data anonymization - p. 165 12. Chapter 6 Transport planning and big data - p. 171 13. Chapter 7 Data-driven mobility management - p. 205 14. Chapter 8 Digital twin - p. 223 15. Chapter 9 Summary - p. 239 16. List of acronyms - p. 247 17. Index - p. 251
Smart Urban Mobility: Transport Planning in the Age of Big Data and Digital Twins explores the data-driven paradigm shift in urban mobility planning and examines how well-established practices and strong data analytics efforts can be better aligned to fit transport planning practices and "smart" mobility management needs. The book provides a comprehensive survey of the major big data and technology resources derived from smart cities research which are collectively poised to transform urban mobility. Chapters highlight the important aspects of each data source affecting applicability, along with the outcomes of smart mobility measures and campaigns.Transport planners, urban policymakers, public administrators, city managers, data scientists, and consulting companies managing smart city interventions and data-driven urban transformation projects will gain a better understanding of this up-and-coming research from this book’s detailed overview and numerous practical examples and best practices for operational deployment.
1. Chapter 1 Introduction - p. 1 2. Chapter 2 Introduction to smart mobility - p. 9 3. Chapter 3 The new challenge of smart urban mobility - p. 25 4. Chapter 4 Small and big data for mobility studies - p. 79 5. Chapter 5 Data analytics - p. 121 6. 5.1: Objectives of the chapter - p. 121 7. 5.2: Word cloud - p. 121 8. 5.3: Data analytics introduction - p. 121 9. 5.4: Data analytics workflow - p. 122 10. 5.5: Machine learning - p. 134 11. 5.6: Data anonymization - p. 165 12. Chapter 6 Transport planning and big data - p. 171 13. Chapter 7 Data-driven mobility management - p. 205 14. Chapter 8 Digital twin - p. 223 15. Chapter 9 Summary - p. 239 16. List of acronyms - p. 247 17. Index - p. 251
