City-scale control of urban road traffic poses a challenging problem. Dynamical models based on the macroscopic fundamental diagram (MFD) enable development of model predictive perimeter control methods for large-scale urban networks, representing an advanced control solution carrying substantial potential for field implementation. In this paper we develop a multi-region approximation of the trip-based model, which describes in more details the trip length characteristics compared to existing accumulation-based models. The proposed M-model includes effects of the total remaining travel distance on the transfer flows driving the vehicle accumulation dynamics, potentially yielding improved accuracy over the standard production-over-trip length approximation of the outflow MFD considered in many works on MFD-based modeling and control. We explain that to properly perform perimeter control, boundary queue dynamics have to be integrated. Furthermore, model-based parameter estimation (MBPE), nonlinear moving horizon observer (MHO), and model predictive control (MPC) formulations for the proposed models are presented, forming an integrated traffic control framework. Microsimulation-based case studies, considering an urban network with 1500 links, where the model parameters obtained by MBPE method are used in MHO and MPC design, demonstrate the efficient operation of the proposed framework.

城市规模的城市道路交通控制提出了一个具有挑战性的问题。基于宏观基本图（MFD）的动力学模型可以开发用于大型城市网络的模型预测性周边控制方法，代表了一种先进的控制解决方案，具有在现场实施的巨大潜力。在本文中，我们开发了基于行程的模型的多区域近似，与现有的基于累积的模型相比，它更详细地描述了行程长度特征。拟议的M模型包括总剩余行驶距离对驱动车辆蓄积动力学的传递流的影响，在许多基于MFD的建模工作中考虑的流出MFD的标准生产跨行长度近似值下，有可能产生更高的精度和控制。我们解释说，要正确执行边界控制，必须集成边界队列动态。此外，针对所提出的模型，提出了基于模型的参数估计（MBPE），非线性移动视界观察器（MHO）和模型预测控制（MPC）公式，从而形成了一个集成的交通控制框架。基于微观模拟的案例研究，考虑了具有1500条链路的城市网络，其中通过MBPE方法获得的模型参数用于MHO和MPC设计，证明了所提出框架的有效运行。形成一个综合的交通控制框架。基于微观模拟的案例研究，考虑了具有1500条链路的城市网络，其中通过MBPE方法获得的模型参数用于MHO和MPC设计，证明了所提出框架的有效运行。形成一个综合的交通控制框架。基于微观模拟的案例研究，考虑了具有1500条链路的城市网络，其中通过MBPE方法获得的模型参数用于MHO和MPC设计，证明了所提出框架的有效运行。