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Forecasting, simulation and PIP control of interurban traffic networks

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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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/ISSN › Conference contribution/Paper › peer-review

Harvard

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

APA

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

Vancouver

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

Author

Taylor, James ; Young, Peter ; Chotai, Arunkumar. / Forecasting, simulation and PIP control of interurban traffic networks. 12th International Conference on Systems Engineering. 1997.

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 -