Optimal Perimeter Control for Two Urban Regions With Macroscopic Fundamental Diagrams: A Model Predictive Approach

TLDR

Urban traffic studies reveal that macroscopic fundamental diagrams (MFDs) describe a unimodal, low‑scatter relationship between network vehicle density and space‑mean flow for homogeneous regions. The study formulates optimal perimeter control for two‑region urban cities using macroscopic fundamental diagrams. The authors design border‑based controllers that adjust inter‑region flow percentages to maximize trip completion, solving the problem with model predictive control using MFD‑derived prediction and plant models, and evaluate robustness across congestion levels, MFD errors, demand noise, and smoothing techniques. Model predictive control outperforms greedy feedback control and can be extended to hierarchical strategies for heterogeneously congested cities.

Abstract

Recent analysis of empirical data from cities showed that a macroscopic fundamental diagram (MFD) of urban traffic provides for homogenous network regions a unimodal low-scatter relationship between network vehicle density and network space-mean flow. In this paper, the optimal perimeter control for two-region urban cities is formulated with the use of MFDs. The controllers operate on the border between the two regions and manipulate the percentages of flows that transfer between the two regions such that the number of trips that reach their destinations is maximized. The optimal perimeter control problem is solved by model predictive control, where the prediction model and the plant (reality) are formulated by MFDs. Examples are presented for different levels of congestion in the regions of the city and the robustness of the controller is tested for different sizes of error in the MFDs and different levels of noise in the traffic demand. Moreover, two methods for smoothing the control sequences are presented. Comparison results show that the performances of the model predictive control are significantly better than a "greedy" feedback control. The results in this paper can be extended to develop efficient hierarchical control strategies for heterogeneously congested cities.