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

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Description

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

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
05 November 2020
Listed Since
01 October 2019

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