On-line Calibration for Dynamic Traffic Assignment Models: Theory, Methods and Application - Couverture souple

Antoniou, Constantinos

Couverture souple

ISBN 10 : 3836421410 ISBN 13 : 9783836421416

Editeur : VDM Verlag Dr. Mueller E.K., 2007

Synopsis

Traffic estimation and prediction (or dynamic traffic assignment) models are expected to contribute to the reduction of travel time delays. In this book, an on-line calibration approach that jointly estimates all model parameters is presented. The methodology imposes no restrictions on the models, the parameters or the data that can be handled, and emerging or future data can be easily incorporated. The modeling approach is applicable to any simulation model and is not restricted to the application domain covered in this book. Several modified, non-linear Kalman Filter methodologies are presented, e.g. Extended Kalman Filter (EKF), Iterated EKF, Limiting EKF, and Unscented Kalman Filter. Extensive case studies on freeway networks in Europe and the US are used to demonstrate the approach, to verify the importance of on-line calibration, and to test the presented algorithms. The main target audience of this book comprises Intelligent Transportation Systems researchers and graduate students, as well as practitioners, including Metropolitan Planning Organization engineers and Traffic Management Center operators, and any reader with an interest in dynamic state and parameter estimation.

A propos du livre

Présentation de l'éditeur

Revision with unchanged content. Traffic estimation and prediction (or dynamic traffic assignment) models are expected to contribute to the reduction of travel time delays. In this book, an on-line calibration approach that jointly estimates all model parameters is presented. The methodology imposes no restrictions on the models, the parameters or the data that can be handled, and emerging or future data can be easily incorporated. The modeling approach is applicable to any simulation model and is not restricted to the application domain covered in this book. Several modified, non-linear Kalman Filter methodologies are presented, e.g. Extended Kalman Filter (EKF), Iterated EKF, Limiting EKF, and Unscented Kalman Filter. Extensive case studies on freeway networks in Europe and the US are used to demonstrate the approach, to verify the importance of on-line calibration, and to test the presented algorithms. The main target audience of this book comprises Intelligent Transportation Systems researchers and graduate students, as well as practitioners, including Metropolitan Planning Organization engineers and Traffic Management Center operators, and any reader with an interest in dynamic state and parameter estimation.

Biographie de l'auteur

Dr. Constantinos AntoniouPost-doctoral Research Associate, Massachusetts Institute of Technology (MIT). Diploma in Civil Eng. (1995, National Technical. Univ. of Athens); M.S. in Transportation (1997, MIT); Ph.D. in Transportation Systems (2004, MIT). He has published more than 50 peer-reviewed scientific articles. Contact him at costas@mit.edu.

Détails de l'édition

• Éditeur: VDM Verlag Dr. Mueller E.K.
• Date d'édition: 2007
• Langue: anglais
• ISBN 10: 3836421410
• ISBN 13: 9783836421416
• Reliure: Broché
• Nombre de pages: 160
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible