Application of Model Predictive Control to Traffic Network Systems Based on Hierarchical Distributed Control Framework

Traffic congestion is the chronic problem which degrades an urban traffic sustainable development. If the public infrastructure, logistics, and the development of a public transport system planning are advanced, they will reduce the traffic congestion problems in the urban city and improve the traffic flow in each intersection. This paper aims to establish the traffic model predictive control method with the hierarchical distributed control framework. The traffic controller is composed of three layers which are network layer, area layer, and intersection layer. We develop the hierarchical distributed model predictive control (HDMPC) to improve the performance of hierarchical distributed control (HDC). Finally, numerical examples are demonstrate the HDMPC method is significantly improve the traffic flow over the HDC on the example scenario.