Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory
Language: English
Published by Elsevier Science Publishing Co Inc, 2020
- Softcover
- Used
Seller: World of Books Inc, Montgomery, IL, U.S.A.World of Books Inc
AbeBooks seller since March 23, 2026
Condition: Used - Good
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Add to basketItem description from seller
Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory shifts the current focus from using modeling and simulation data for traffic measurements to the use of actual data. The book uses real-world, empirically-derived data from a large fleet of connected vehicles, local observations and aerial observation to shed light on key traffic phenomena. Readers will learn how to develop an understanding of the empirical features of vehicular traffic networks and how to consider these features in emerging, intelligent transport systems. Topics cover congestion patterns, fuel consumption, the influence of weather, and much more. This book offers a unique, data-driven analysis of vehicular traffic in traffic networks, also considering how to apply data-driven insights to the intelligent transport systems of the future.
Seller Inventory # CIN0128191384G
- Title
- Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory
- Author
- Hubert Rehborn
- Publisher
- Elsevier Science Publishing Co Inc
- Publication year
- 2020
- Condition
- Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0128191384
- ISBN 13
- 9780128191385
Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory shifts the current focus from using modeling and simulation data for traffic measurements to the use of actual data. The book uses real-world, empirically-derived data from a large fleet of connected vehicles, local observations and aerial observation to shed light on key traffic phenomena. Readers will learn how to develop an understanding of the empirical features of vehicular traffic networks and how to consider these features in emerging, intelligent transport systems. Topics cover congestion patterns, fuel consumption, the influence of weather, and much more.
This book offers a unique, data-driven analysis of vehicular traffic in traffic networks, also considering how to apply data-driven insights to the intelligent transport systems of the future.
- Provides an empirically-driven analysis of traffic measurements/congestion based on real-world data collected from a global fleet of vehicles
- Applies Kerner’s three-phase traffic theory to empirical data
- Offers a critical scientific understanding of the underlying concerns of traffic control in automated driving and intelligent transport systems
"Synopsis" may belong to another edition of this title.
About the Author
Micha Koller is a traffic researcher at Daimler AG responsible for the worldwide operation and development of traffic services. He has a doctorate in Computer Science from the University of Tübingen, holds more than 30 patents, and has published widely in the field.
Consultant, Germany
"About the title" may belong to another edition of this title.
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