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Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more.
- Author:
- Ziqiang Zeng, Yinhai Wang
- Publisher:
- Elsevier
- Publication Date:
- Dec 05, 2018
- Number of pages:
- 299 pages
- Language:
- English
- Binding:
- Paperback
- ISBN-10:
- 0128170263
- ISBN-13:
- 9780128170267