Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory
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
1137580404
Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory
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
125.0 In Stock
Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory

Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory

Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory

Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory

eBook

$125.00 

Available on Compatible NOOK devices, the free NOOK App and in My Digital Library.
WANT A NOOK?  Explore Now

Related collections and offers


Overview

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

Product Details

ISBN-13: 9780128191392
Publisher: Elsevier Science
Publication date: 10/23/2020
Sold by: Barnes & Noble
Format: eBook
Pages: 192
File size: 56 MB
Note: This product may take a few minutes to download.

About the Author

Hubert Rehborn is a traffic researcher at Daimler AG where he investigates the future of traffic as part of connected navigations systems. His doctorate in Electrical Engineering is from the University of Hagen, and he holds more than 135 patents, and has authored more than 60 papers in the field.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

Table of Contents

1. Introduction2. How Traffic Congestion can be measured3. Analysis of Congested Traffic Pattern Features on Freeways4. Analysis of Congested Traffic Patterns in Urban Areas5. Applications of Traffic in Transportation Science6. Future Directions7. Bibliography

What People are Saying About This

From the Publisher

Shows how to more accurately analyze traffic measurements and congestion more accurately using empirically driven data from connected vehicles, sensors and drones

From the B&N Reads Blog

Customer Reviews