Feedback Perimeter Control for Heterogeneous Urban Networks Using Adaptive Optimization

Abstract

A control scheme for heterogeneous transportation networks is presented. The methodology is based on the concept of the Macroscopic Fundamental Diagram (MFD) integrated with an adaptive optimization technique. The heterogeneous transportation network is first partitioned into a number of regions with homogeneous traffic conditions and well-defined MFDs. A macroscopic MFD-based model is used to describe the traffic dynamics of the resulting multi-region transportation system. A multivariable proportional integral (PI) feedback regulator is implemented to control the nonlinear system in real-time. The control variables consist of the inter-transferring flows between neighbourhood regions and the actuators correspond to the traffic lights of these areas (e.g. boundaries between regions). The recently proposed Adaptive Fine-Tuning (AFT) algorithm is used to optimize the gain matrices as well as the vector with the set-points of the PI controller. AFT is an iterative adaptive algorithm that optimizes the values of the tuneable parameters of the controller (e.g. gains and set-points) based on measurements of a performance index (e.g. total delay) for different perturbations of the parameters. The overall control scheme is tested in simulation and different performance criteria are studied. The performance of a fixed-time policy is compared to the final controller that is obtained after the convergence of AFT.