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Distributed Model Predictive Control Method for Optimal Coordination of Signal Splits in Urban Traffic Networks
Author(s) -
Ye BaoLin,
Wu Weimin,
Mao Weijie
Publication year - 2015
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1011
Subject(s) - model predictive control , benchmark (surveying) , computer science , traffic flow (computer networking) , nonlinear system , signal (programming language) , traffic generation model , computational complexity theory , dual (grammatical number) , control (management) , control theory (sociology) , distributed computing , control engineering , engineering , real time computing , algorithm , artificial intelligence , computer network , art , physics , literature , geodesy , quantum mechanics , programming language , geography
Coordination and control approaches based on model predictive control (MPC) have been widely investigated for traffic signal control in urban traffic networks. However, due to the complex non‐linear characters of traffic flows and the large scale of traffic networks, a basic challenge faced by these approaches is the high online computational complexity. In this paper, to reduce the computational complexity and improve the applicability of traffic signal control approaches based on MPC in practice, we propose a distributed MPC approach (DCA‐MPC) to coordinate and optimize the signal splits. Instead of describing the dynamics of traffic flow within each link of the traffic network with a simplified linear model, we present an improved nonlinear traffic model. Based on the nonlinear model, an MPC optimization framework for the signal splits control is developed, whereby the interactions between subsystems are accurately modeled by employing two interconnecting constraints. In addition, by designing a novel dual decomposition strategy, a distributed coordination algorithm is proposed. Finally, with a benchmark traffic network, experimental results are given to illustrate the effectiveness of the proposed method.