A traffic responsive control framework for signalized junctions based on hybrid traffic flow representation

The paper proposes a traffic responsive control framework based on a Model Predictive Control (MPC) approach. The framework focuses on a centralized method, which can simultaneously compute the network decision variables (i.e., the green timings at each junction and the offset of the traffic light p...

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Bibliographic Details
Published in:Journal of intelligent transportation systems 2023-09, Vol.27 (5), p.606-625
Main Authors: Storani, Facundo, Di Pace, Roberta, De Schutter, Bart
Format: Article
Language:English
Subjects:
Adaptive control
Cellular automata
Disaggregate models
Interacting junctions
model predictive control
network
Prediction models
Predictive control
Traffic control
Traffic flow
traffic flow model
traffic lights
Traffic models
Traffic signals
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Summary:The paper proposes a traffic responsive control framework based on a Model Predictive Control (MPC) approach. The framework focuses on a centralized 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 signalized 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.
ISSN:1547-2450
1547-2442
DOI:10.1080/15472450.2022.2074790