Big Data and Mobility as a Service (eBook, ePUB)

Redaktion: Zhang, Haoran; Shibasaki, Ryosuke; Song, Xuan

• Format: ePub

Produktbeschreibung

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.

• Summarizes current fundamental MaaS technologies
• Shows how to utilize anonymous big data for transportation analysis and problem-solving
• Illustrates, with data-enabled shared transportation service examples from different countries, the similarities and differences within a global urban mobility framework

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 306
• Erscheinungstermin: 1. Oktober 2021
• Englisch
• ISBN-13: 9780323901703
• Artikelnr.: 62663852

Autorenporträt

Haoran (Ronan) Zhang is Assistant Professor in the Center for Spatial Information Science at the University of Tokyo, a Researcher at the School of Business Society and Engineering at Mälardalen University in Sweden, and Senior Scientist at Locationmind Inc. in Japan. His research includes smart supply chain technologies, GPS data in shared transportation, urban sustainable performance, GIS technologies in renewable energy systems, and smart cities. He is author of numerous journal articles and Editorial Board Member of several international academic journals. He has Ph.D.'s in both Engineering and Sociocultural Environment and was awarded Excellent Young Researcher by Japan's Ministry of Education, Culture, Sports, Science and Technology.

Inhaltsangabe

1. Big Data and MaaS
2. MaaS system Development and APPs
3. Spatio-temporal Data Pre-processing Technologies
4. Travel Similarity Estimation and Clustering
5. Data Fusion Technologies for MaaS
6. Data-driven Optimization Technologies for MaaS
7. Data-driven Estimation for Urban Travel Shareability
8. MaaS system Data mining Technologies
9. IoT Technologies for MaaS
10. MaaS System Visualization
11. MaaS for Urban Sustainable Development