Data Analytics for Intelligent Transportation Systems, Second Edition provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Other sections provide extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies.
All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. In addition, they will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning.
Key Features
- Utilizes real ITS examples to facilitate a quicker grasp of materials presented
- Contains contributors from both leading academic and commercial domains
- Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications
- Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques
- New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics
2. Data Analytics: Fundamentals
3. Data Science Tools and Techniques to Support Data Analytics in Transportation Applications
4. The Centrality of Data: Data Lifecycle and Data Pipelines
5. Data Infrastructure for Intelligent Transportation Systems
6. Security and Data Privacy of Modern Automobiles
7. Interactive Data Visualization
8. Data Analytics in Systems Engineering for Intelligent Transportation Systems
9. Data Analytics for Safety Applications
10. Data Analytics for Intermodal Freight Transportation Applications
11. Social Media Data in Transportation
12. Machine Learning in Transportation Data Analytics
13. Quantum Computing in Data Analytics, Mashrur Chowdhury
14. Society and Environment in ITS Data Analytics