Coalitional Model Predictive Control on Freeways Traffic Networks

Abstract

This paper discusses the application of coalitional model predictive control (MPC) to freeways traffic networks, where the goal is reducing the time spent by the drivers through a dynamic setting of variable speed limits (VSL) and ramp metering. The prediction model METANET is used to represent the traffic flows evolution. The system behavior and objective function lead to a non-convex and non-linear optimization problem, which can only be solved in a centralized fashion for small networks. The underlying motivation of this paper is the continued advance of clustering methods in the control of largescale and spatially distributed systems. The global freeway system is partitioned into a set of coupled sub-stretches, which in turn are assigned to the different agents involved in the control problem. These local controllers can dynamically assemble into coalitions to take coordinated measures. In this work, a top-down approach is considered: the bottom layer consists of the set of controllers that compute the VSL and ramp-metering across time; and the supervisory layer changes periodically the information exchange structure to promote coalitions of those controllers that bring greater performance to the global system. In this way, a balance is sought between optimality and efficiency. Finally, the coalitional approach is simulated on a stretch of traffic freeway where cooperation with adjacent sub-stretches is allowed.Index Terms-Distributed model predictive control, coalitional control, control by clustering, traffic systems.

Research on the Influence of the Coupling Coordination of the Logistics Industry and Manufacturing Industry on the Upgrading of the Manufacturing Industry

“…The coupling coordination degree is the horizontal embodiment of mutual promotion and benign interaction between systems. In recent years, the theory of coupling coordination has been widely used in many fields of transportation, such as control operation strategy [24], planning strategy [25], predictive control and so on [26]. In the composite system composed of the logistics industry and manufacturing industry, the coordinated development of two industries refers to the evolution of two subsystems and their components in a harmonious and consistent direction, and the coupling of two industries refers to the mutual influence and interaction between two subsystems and their components.…”

Distributed Model Predictive Control for Tracking: A Coalitional Clustering Approach

“…The underlying goal of these schemes is to enable communication only among highly coupled agents so as to obtain a performance close to a fully coordinated system, but reducing the complexity of the control problem and the cooperation efforts, thus improving the scalability. This idea has interesting connections with cooperative game theory [9], [10] and has been extended to the well-known framework of model predictive control (MPC) [11], considering applications where the coupling varies in time and space, such as irrigation canals [12] and traffic freeways [13]. Similar approaches have also been recently proposed for dealing with large-scale power systems, e.g., in [14], a distribution network is split into control areas to solve a voltage regulation problem in an admissible time; in [2], the communication topology switches according to the oscillation modes; and in [15], a wind farm is split up into subsets of wind turbines according to the wake coupling effect.…”

A light clustering model predictive control approach to maximize thermal power in solar parabolic-trough plants

“…Maestre and Ishii (2017) present a fully distributed method where the cooperation architecture is given by link requests/offers between local controllers; and in (Fele et al, 2018), agents perform an autonomous negotiation protocol to determine the partition of the system using coalitional MPC. Potential applications for clustering are power networks (Dörfler et al, 2014;Schiffer et al, 2017), freeways traffic systems (Chanfreut et al, 2020), wind farms (Yuan et al, 2018), telecommunication networks (Masero et al, 2020), irrigation canals (Fele et al, 2014), mobile social networks (Niyato et al, 2011), and supply chains (Gao et al, 2017). To the best of our knowledge, there are no applications in solar parabolic-trough plants.…”