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Data Analytics for Intelligent Transportation Systems

  • 2nd Edition - November 2, 2024
  • Latest edition
  • Editors: Mashrur Chowdhury, Kakan Dey, Amy Apon
  • Language: English

Data Analytics for Intelligent Transportation Systems, Second Edition provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), in… Read more

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Description

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

Readership

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

Table of contents

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

Product details

  • Edition: 2
  • Latest edition
  • Published: November 2, 2024
  • Language: English

About the editors

MC

Mashrur Chowdhury

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.

KD

Kakan Dey

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
Associate Professor, Michigan State University, USA

AA

Amy Apon

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, School of Computing, Clemson University, USA

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