Reference
F. Storani, R. Di Pace, and B. De Schutter, "A traffic responsive control
framework for signalized junctions based on hybrid traffic flow
representation,"
Journal of Intelligent Transportation
Systems, vol. 27, no. 5, pp. 606-625, 2023.
Abstract
The paper proposes a traffic responsive control framework based on a Model
Predictive Control (MPC) approach. The framework focuses on a centralised
method, which can simultaneously compute the network decision variables (i.e.,
the green timings at each junction and the offset of the traffic light plans of
the network). Furthermore, the framework is based on a hybrid traffic flow
model operating as a prediction model and plant model in the control procedure.
The hybrid traffic flow model combines two sub-models: an aggregate model
(i.e., the Cell Transmission Model; CTM) and a disaggregate model (i.e., the
Cellular Automata model; CA), using a transition cell to connect them. The
whole framework is tested on a signalised arterial, performing several analyses
to calibrate the MPC strategy and evaluate the traffic control approach using
fixed and adaptive control strategies. All analyses are made in terms of total
time spent, network total delay, queue lengths and degree of saturation.
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BibTeX
@article{StoDiP:23-002,
author = {Storani, Facundo and Di Pace, Roberta and De Schutter, Bart},
title = {A Traffic Responsive Control Framework for Signalized Junctions
Based on Hybrid Traffic Flow Representation},
journal = {Journal of Intelligent Transportation Systems},
volume = {27},
number = {5},
pages = {606--625},
year = {2023}
}