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On-line Calibration for Dynamic Traffic Assignment models | Theory, methods and application | Constantinos Antoniou | Taschenbuch | 160 S. | Englisch | 2012 | AV Akademikerverlag | EAN 9783639413090 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de ref. del artículo 106443386
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.
Reseña del editor: 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.
Título: On-line Calibration for Dynamic Traffic ...
Editorial: AV Akademikerverlag
Año de publicación: 2012
Encuadernación: Taschenbuch
Condición: Neu