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.

Volume 1: Data Preprocessing and Visualization focuses on how to efficiently pre-process mobile big data to extract and utilize critical feature information of high-dimensional city people flow. It first provides a conceptual theory and framework, then goes on to discuss data sources, trajectory map-matching, noise filtering, trajectory data segmentation, data quality assessment and more. It concludes with a chapter on privacy protection in mobile big data mining.

Volume 2: Mobility Analytics and Prediction provides a basis for how to simulate and predict mobility data. After an introductory theory chapter, it then covers crucial topics such as long-term mobility pattern analytics, mobility data generators, user information inference, Grid-based population density prediction, and more. It concludes with a chapter on graph-based mobility data analytics.

Volume 3: Mobility Data-driven Applications looks at various cases studies to illustrate and explore the methods introduced in the first two volumes. It begins with a set of chapters on Intelligent Transportation Management, using cases of dynamic road pricing, P2P bidding systems, bicycle-sharing systems, ride-sharing simulation, and customized bus systems. Part 2 then discusses Smart Emergency Management, detailing cases such as the Fukushima Earthquake, Hurricane Katrina, and COVID-19. Part 3 concludes with a set of chapters on Urban Sustainability Development, covering bicycle travel behavior, railway travel behavior, mobility inequality, and both road and light pollution inequality.

城市系统是一城市系统是一个十分复杂的有机整体，在其内部不断地进行物质流、能量流、人员流、信息流的交换。仅仅研究单一城市及其内部空间的差异，不能揭示城市本质和其发展的规律性，需要开展城市系统优化才能揭示城市的实质和作用。系统工程正是以复杂系统为研究对象，着手解决复杂系统问题的学科。因此，本课程将研究对象界定为城市系统，并借鉴系统科学相关理论，对城市系统优化相关理论与方法进行论述。