Cover for Data-Driven Traffic Engineering

Data-Driven Traffic Engineering

Understanding of Traffic and Applications Based on Three-Phase Traffic Theory

Book2021

Authors:

Hubert Rehborn, Micha Koller and Stefan Kaufmann

Data-Driven Traffic Engineering

Understanding of Traffic and Applications Based on Three-Phase Traffic Theory

Book2021

 

Cover for Data-Driven Traffic Engineering

Authors:

Hubert Rehborn, Micha Koller and Stefan Kaufmann

About the book

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Book 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 ... read full description

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  1. Full text access
  2. Book chapterNo access

    Chapter 1 - Introduction

    Pages 1-4

  3. Book chapterAbstract only

    Chapter 2 - How traffic data are measured

    Pages 5-28

  4. Book chapterAbstract only

    Chapter 3 - Analysis of congested traffic pattern features on freeways: A historical overview

    Pages 29-64

  5. Book chapterAbstract only

    Chapter 4 - Congested traffic patterns in urban areas

    Pages 65-83

  6. Book chapterAbstract only

    Chapter 5 - Applications of traffic in transportation science

    Pages 85-169

  7. Book chapterNo access

    Chapter 6 - Future directions

    Pages 171-174

  8. Book chapterNo access

    Index

    Pages 175-179

About the book

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.

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.

Key Features

  • 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
  • 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

Details

ISBN

978-0-12-819138-5

Language

English

Published

2021

Copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

Imprint

Elsevier

Authors

Hubert Rehborn

Micha Koller

Stefan Kaufmann