Road Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. The book examines commonly used traffic analysis methodologies as well the emerging methods that use deep learning methods. Other sections discuss how to understand statistical models and machine learning algorithms and how to apply them to traffic modeling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, this book is ideal for researchers and practitioners who want to improve the performance of intelligent transportation systems.

Provides integrated, up-to-date and complete coverage of the key components for intelligent transportation systems: traffic modeling, forecasting, estimation and monitoring
Uses methods based on video and time series data for traffic modeling and forecasting
Includes case studies, key processes guidance and comparisons of different methodologies

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Yes, you can access Road Traffic Modeling and Management by Fouzi Harrou,Abdelhafid Zeroual,Mohamad Mazen Hittawe,Ying Sun in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Transportation & Navigation. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Elsevier

Year

2021

ISBN

9780128234334

Topic

Technology & Engineering

Subtopic

Transportation & Navigation

Index

Technology & Engineering

Cover image
Title page
Table of Contents
Copyright
Chapter 1: Introduction
Chapter 2: Road traffic modeling
Chapter 3: Road traffic density estimation
Chapter 4: Model-based techniques for traffic congestion detection
Chapter 5: Traffic congestion detection: data-based techniques
Chapter 6: Recurrent and convolutional neural networks for traffic management
Chapter 7: Conclusion and further research directions
Index