Online set-point estimation for feedback-based traffic control applications
This paper deals with traffic control at motorway bottlenecks assuming the existence of an unknown, time-varying, Fundamental Diagram (FD). The FD may change over time due to different traffic compositions, e.g., light and heavy vehicles, as well as in the presence of connected and automated vehicles equipped with different technologies at varying penetration rates, leading to inconstant and uncertain driving characteristics. A novel methodology, based on Model Reference Adaptive Control, is proposed to robustly estimate in real-time the time-varying set-points that maximise the bottleneck throughput, particularly useful when the traffic is regulated via a feedback-based controller. Furthermore, we demonstrate the global asymptotic stability of the proposed controller through a Lyapunov analysis. The effectiveness of the proposed approach is evaluated via simulation experiments, where the estimator is integrated into a feedback ramp-metering control strategy, employing a second-order multi-lane macroscopic traffic flow model, modified to account for time-varying FDs.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Proximal Policy Optimization Learning based Control of Congested Freeway Traffic
This study proposes a delay-compensated feedback controller based on proximal policy optimization (PPO) reinforcement learning to stabilize traffic flow in the congested regime by manipulating the time-gap of adaptive cr…
Adaptive Real-Time Grid Operation via Online Feedback Optimization with Sensitivity Estimation
In this paper we propose an approach based on an Online Feedback Optimization (OFO) controller with grid input-output sensitivity estimation for real-time grid operation, e.g., at subsecond time scales. The OFO controlle…
SensitivityFeedback-feedforward Signal Control with Exogenous Demand Estimation in Congested Urban Road Networks
To cope with uncertain traffic patterns and traffic models, traffic-responsive signal control strategies in the literature are designed to be robust to these uncertainties. These robust strategies still require sensing i…
Traffic Signal ControlClosing the Loop: Dynamic State Estimation and Feedback Optimization of Power Grids
This paper considers the problem of online feedback optimization to solve the AC Optimal Power Flow in real-time in power grids. This consists in continuously driving the controllable power injections and loads towards t…
State EstimationRobust output feedback model predictive control using online estimation bounds
We present a framework to design nonlinear robust output feedback model predictive control (MPC) schemes that ensure constraint satisfaction under noisy output measurements and disturbances. We provide novel estimation m…
Model Predictive Control