Road Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning

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 INDICE: 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

• ISBN: 978-0-12-823432-7
• Editorial: Elsevier
• Encuadernacion: Rústica
• Páginas: 268
• Fecha Publicación: 08/10/2021
• Nº Volúmenes: 1
• Idioma: Inglés