A Data-Driven Iterative Feedback Tuning Approach of ALINEA for Freeway Traffic Ramp Metering With PARAMICS Simulations

In this work, a new iterative feedback tuning approach is proposed to tune ALINEA's controller gain automatically when there is not enough prior information available to select a proper feedback gain of ALINEA. It is a data-driven method and the ALINEA controller is auto-tuned only depending on the input and output data collected from closed-loop experiments. To mimic a real traffic environment, a simulator is built on the PARAMICS platform. The flow-based ALINEA controller is also considered to illustrate the good tuning performance of IFT comprehensively. The effectiveness of the proposed methods is verified through PARAMICS based simulations.