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Forecasting, simulation and PIP control of interurban traffic networks

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Forecasting, simulation and PIP control of interurban traffic networks. / Taylor, James; Young, Peter; Chotai, Arunkumar.

12th International Conference on Systems Engineering. 1997.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Taylor J, Young P, Chotai A. Forecasting, simulation and PIP control of interurban traffic networks. In 12th International Conference on Systems Engineering. 1997

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Bibtex

@inproceedings{9252841c2e5c4160b297dd7f1e9f3eb7,
title = "Forecasting, simulation and PIP control of interurban traffic networks",
abstract = "This paper discusses a number of research areas concerned with dynamic traffic management, including forecasting, simulation and, ultimately, control of motorway traffic flow. A detailed non-linear simulation of the Amsterdam A10 west ring road, utilising a dynamic state space representation called the Statistical Traffic Model (STM) is described. The simulation is employed in the development of a robust, co-ordinated ramp metering system, based on the Non-Minimal State Space (NMSS) approach to control design, which yields adaptive Proportional-Integral-Plus (PIP) controllers. Finally, when employed in predictive mode, the STM requires forecasts of the on-ramp inputs to the motorway. One approach to obtaining such univariate forecasts, namely Dynamic Harmonic Regression (DHR) is also discussed.",
keywords = "non-minimal state space, proportional-integral plus, co-ordinated traffic control, dynamic harmonic regression model, non-linear simulation",
author = "James Taylor and Peter Young and Arunkumar Chotai",
year = "1997",
language = "English",
booktitle = "12th International Conference on Systems Engineering",

}

RIS

TY - GEN

T1 - Forecasting, simulation and PIP control of interurban traffic networks

AU - Taylor, James

AU - Young, Peter

AU - Chotai, Arunkumar

PY - 1997

Y1 - 1997

N2 - This paper discusses a number of research areas concerned with dynamic traffic management, including forecasting, simulation and, ultimately, control of motorway traffic flow. A detailed non-linear simulation of the Amsterdam A10 west ring road, utilising a dynamic state space representation called the Statistical Traffic Model (STM) is described. The simulation is employed in the development of a robust, co-ordinated ramp metering system, based on the Non-Minimal State Space (NMSS) approach to control design, which yields adaptive Proportional-Integral-Plus (PIP) controllers. Finally, when employed in predictive mode, the STM requires forecasts of the on-ramp inputs to the motorway. One approach to obtaining such univariate forecasts, namely Dynamic Harmonic Regression (DHR) is also discussed.

AB - This paper discusses a number of research areas concerned with dynamic traffic management, including forecasting, simulation and, ultimately, control of motorway traffic flow. A detailed non-linear simulation of the Amsterdam A10 west ring road, utilising a dynamic state space representation called the Statistical Traffic Model (STM) is described. The simulation is employed in the development of a robust, co-ordinated ramp metering system, based on the Non-Minimal State Space (NMSS) approach to control design, which yields adaptive Proportional-Integral-Plus (PIP) controllers. Finally, when employed in predictive mode, the STM requires forecasts of the on-ramp inputs to the motorway. One approach to obtaining such univariate forecasts, namely Dynamic Harmonic Regression (DHR) is also discussed.

KW - non-minimal state space

KW - proportional-integral plus

KW - co-ordinated traffic control

KW - dynamic harmonic regression model

KW - non-linear simulation

M3 - Conference contribution/Paper

BT - 12th International Conference on Systems Engineering

ER -