Big Data and Mobility as a Service explores MaaS platforms that can be adaptable to the ever-evolving mobility environment. It looks at multi-mode urban crowd data to assess urban mobility characteristics, their shared transportation potential, and their performance conditions and constraints. The book analyzes the roles of multimodality, travel behavior, urban mobility dynamics and participation. Combined with insights on using big data to analyze market and policy decisions, this book is an essential tool for urban transportation management researchers and practitioners.
1. Introduction - p. Page v 2. List of Illustrations - p. Page viii 3. List of Tables - p. Page ix 4. Chapter 1 : MaaS system development and APPs - p. Page ix 5. Chapter 2 : Spatio-temporal data preprocessing technologies - p. Page 23 6. Chapter 3 : Travel similarity estimation and clustering - p. Page 69 7. Chapter 4 : Data fusion technologies for MaaS - p. Page 107 8. Chapter 5 : Data-driven optimization technologies for MaaS - p. Page 137 9. Chapter 6 : Data-driven estimation for urban travel shareability - p. Page 171 10. Chapter 7 : Data mining technologies for Mobility-as-a-Service (MaaS) - p. Page 200 11. Chapter 8 : MaaS and IoT: Concepts, methodologies, and applications - p. Page 228 12. Chapter 9 : MaaS system visualization - p. Page 241 13. Chapter 10 : MaaS for sustainable urban development - p. Page 262 14. Index - p. Page 278
Big Data and Mobility as a Service explores MaaS platforms that can be adaptable to the ever-evolving mobility environment. It looks at multi-mode urban crowd data to assess urban mobility characteristics, their shared transportation potential, and their performance conditions and constraints. The book analyzes the roles of multimodality, travel behavior, urban mobility dynamics and participation. Combined with insights on using big data to analyze market and policy decisions, this book is an essential tool for urban transportation management researchers and practitioners.
1. Introduction - p. Page v 2. List of Illustrations - p. Page viii 3. List of Tables - p. Page ix 4. Chapter 1 : MaaS system development and APPs - p. Page ix 5. Chapter 2 : Spatio-temporal data preprocessing technologies - p. Page 23 6. Chapter 3 : Travel similarity estimation and clustering - p. Page 69 7. Chapter 4 : Data fusion technologies for MaaS - p. Page 107 8. Chapter 5 : Data-driven optimization technologies for MaaS - p. Page 137 9. Chapter 6 : Data-driven estimation for urban travel shareability - p. Page 171 10. Chapter 7 : Data mining technologies for Mobility-as-a-Service (MaaS) - p. Page 200 11. Chapter 8 : MaaS and IoT: Concepts, methodologies, and applications - p. Page 228 12. Chapter 9 : MaaS system visualization - p. Page 241 13. Chapter 10 : MaaS for sustainable urban development - p. Page 262 14. Index - p. Page 278
