In this paper a new model for urban traffic control is presented. An urban area, composed of elementary components such as priority controlled intersections, simple road links, road links with on-ramps and off-ramps and intersections controlled by traffic lights, can be modelled as a discrete event system. In this work we use a modular and hybrid approach, where coloured timed Petri net models allow a microscopic representation for some parts of the network, while coarser, more aggregated models are used for other parts. One of the main aims in urban traffic control is to maximize the throughput of the system by means of real-time actions. One can, for example, maximize the network throughput by dynamically adapting the signal timings in response to changing traffic demand and by coordinating the operation of adjacent signals. The proposed hybrid model may be easily implemented in a simulation routine that is useful for state estimation and for model predictive control.

A Hybrid Model for Urban Traffic Control

BASILE, FRANCESCO;CHIACCHIO, Pasquale
2004-01-01

Abstract

In this paper a new model for urban traffic control is presented. An urban area, composed of elementary components such as priority controlled intersections, simple road links, road links with on-ramps and off-ramps and intersections controlled by traffic lights, can be modelled as a discrete event system. In this work we use a modular and hybrid approach, where coloured timed Petri net models allow a microscopic representation for some parts of the network, while coarser, more aggregated models are used for other parts. One of the main aims in urban traffic control is to maximize the throughput of the system by means of real-time actions. One can, for example, maximize the network throughput by dynamically adapting the signal timings in response to changing traffic demand and by coordinating the operation of adjacent signals. The proposed hybrid model may be easily implemented in a simulation routine that is useful for state estimation and for model predictive control.
2004
0780385667
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/1001961
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