Road Traffic Modeling and Management
Using Statistical Monitoring and Deep Learning

Applies deep leaning and advanced statistical methods for more efficient road traffic monitoring, modeling, and forecasting management

Fouzi Harrou (Author), Abdelhafid Zeroual (Author), Mohamad Mazen Hittawe (Author), Ying Sun (Author)

9780128234327, Elsevier Science

Paperback, published 8 October 2021

268 pages
22.9 x 15.2 x 1.8 cm, 0.14 kg

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.

1. Introduction 2. Road Traffic Modeling 3. Road Traffic Density Estimation 4. Traffic Congestion Detection: Model-based Techniques 5. Traffic Congestion Detection: Data-based Techniques 6. Traffic Management: Recurrent and Convolutional Neural Networks 7. Conclusion

Subject Areas: Transport: general interest [WG]