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Data Analytics for Intelligent Transportation Systems
2nd Edition - April 1, 2024
Editors: Mashrur Chowdhury, Amy Apon, Kakan Dey
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Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the… Read more
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Data Analytics for Intelligent Transportation Systems 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. It presents 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. 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.Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners.
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
Exercise problems in each chapter 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
Graduate courses on transportation engineering/intelligent transportation systems; professionals such as those in organizations like the Institute of Transportation Engineers (ITE), American Society of Civil Engineers (ASCE), Institute of Electrical and Electronics Engineers (IEEE), and Intelligent Transportation Society of America (ITS America) Graduate students in data science programs, researchers in transportation engineering, automotive engineering, and computer science domains
1. Characteristics of Intelligent Transportation Systems and Its Relationship With 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
No. of pages: 400
Published: April 1, 2024
Paperback ISBN: 9780443138782
Mashrur Chowdhury is Eugene Douglas Mays Chaired Professor of Transportation in the Glenn Department of Civil Engineering at Clemson University. He is the Director of USDOT Center for Connected Multimodal Mobility and Co-Director of the Complex Systems, Analytics, and Visualization Institute at Clemson. His research focuses on connected and automated vehicles with an emphasis on their integration within smart cities.
Affiliations and expertise
Eugene Douglas Mays Professor of Transportation, Clemson University, USA.
Dr. Amy Apon has been Professor and Chair of the Computer Science Division in the School of Computing at Clemson University since 2011. She was on leave from Clemson as a Program Officer in the Computer Network Systems Division of the National Science Foundation during 2015, working on research programs in Big Data, EXploiting Parallelism and Scalability, and Computer Systems Research. Apon established the High Performance Computing Center at the University of Arkansas and directed the center from 2005 to 2011. She has more than 100 scholarly publications in areas of cluster computing, performance analysis of high performance computing systems, and scalable data analytics. She is a Senior Member of the Association for Computing Machinery and a Senior Member of the Institute of Electrical and Electronics Engineers. Apon holds a Ph.D. in Computer Science from Vanderbilt University.
Affiliations and expertise
Professor and Chair, Computer Science Division, Clemson University, USA
Kakan Dey is Assistant Professor and Director of the Connected and Automated Transportation Systems (CATS) Lab at the West Virginia University. His primary research area is intelligent transportation systems, which include connected and automated vehicle technology, data science, cyber-physical systems, and smart cities.
Affiliations and expertise
Assistant Professor, West Virginia University, USA