
Data Analytics for Intelligent Transportation Systems
Elsevier (Publisher)
Published on 4. April 2017
Book
Paperback/Softback
344 pages
978-0-12-809715-1 (ISBN)
Shipment within 15-20 days
Description
Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of 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. Users will learn 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.
It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn 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.
More details
Language
English
Place of publication
United States
Target group
College/higher education
Intelligent Transportation Systems researchers, practitioners, and graduate students in Transportation and Computer Science.
Product notice
Paperback (trade)
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 18 mm
Weight
597 gr
ISBN-13
978-0-12-809715-1 (9780128097151)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Mashrur Chowdhury | Kakan Dey | Amy Apon
Data Analytics for Intelligent Transportation Systems
Book
11/2024
2nd Edition
Elsevier
€125.50
Shipment within 15-20 days
Additional editions

Mashrur Chowdhury | Amy Apon | Kakan Dey
Data Analytics for Intelligent Transportation Systems
E-Book
04/2017
Elsevier
€119.00
Available for download
Persons
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. 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. 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.
Editor
Eugene Douglas Mays Professor of Transportation, Clemson University, USA.
Professor, School of Computing, Clemson University, USA
Associate Professor, Michigan State University, USA
Content
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
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