Model-Free Adaptive Predictive Control for an Urban Road Traffic Network via Perimeter Control

Zhenxuan Li,Chunye Xu,Shangtai Jin,Jing Li

doi:10.1109/access.2019.2956235

Abstract

This paper proposes a novel model-free adaptive control (MFAC) strategy for urban road traffic network via perimeter control based on dynamic linearization technique and predictive control. The accurate traffic flow model of the urban road network is replaced by equivalent data model. Based on the idea of predictive control, the current control action is obtained by solving online, at each sampling coordinate, a finite horizon closed-loop optimal control problem. The robustness of the MFAC strategy to time-varying desired vehicle accumulation, random traffic demand and macroscopic fundamental diagram (MFD) model uncertainty is verified through simulation results.

Highlights

In the field of traffic engineering, urban road traffic network has become increasingly important
The macroscopic fundamental diagram (MFD) aims at developing aggregate MFD-based models of the traffic flow dynamics for large-scale urban road traffic networks by reducing the modelling complexity
The results show that both PID algorithm and the proposed model-free adaptive predictive boundary control algorithm (MFAPPC) can realize desired vehicle accumulation tracking under complicated scenes

Summary

INTRODUCTION

In the field of traffic engineering, urban road traffic network has become increasingly important. MFD enables the design of elegant control strategies while improving mobility and decreasing delays in large road networks. They were found to firstly describe the dynamics of a congested urban road traffic network in Yokohama (Geroliminis and Daganzo in [2]). It is desirable to design a model-free or data-driven control strategy for phase splits in urban road traffic network. This paper proposed a model-free adaptive control approach for urban road traffic network via perimeter control. A model-free adaptive control algorithm for an urban road traffic network is designed via perimeter control. This paper considers the difference between the control algorithm in theory and practical application to better play the role of control and further achieve the good performance on traffic congestion

PROBLEM FORMUATION

PPD ESTIMATION ALGORITHM AND PREDICTION ALGORITHM

CONCLUSION