系统仿真学报 ›› 2021, Vol. 33 ›› Issue (8): 1875-1881.doi: 10.16182/j.issn1004731x.joss.20-0315

• 仿真建模理论与方法 • 上一篇    下一篇

基于改进宏观交通流模型的MPC算法设计

潘红光, 高磊, 米文毓   

  1. 西安科技大学 电气与控制工程学院,陕西 西安 710054
  • 收稿日期:2020-06-08 修回日期:2020-07-30 发布日期:2021-08-19
  • 作者简介:潘红光(1983-),男,博士,讲师,研究方向为预测控制等。E-mail:hongguangpan@163.com
  • 基金资助:
    国家自然科学基金(61603295)

MPC Algorithm Design Based on Improved Macroscopic Traffic Flow Model

Pan Hongguang, Gao Lei, Mi Wenyu   

  1. College of Electrical and Control Engineering, Xi'an University of Science and Technology, Xi'an 710054
  • Received:2020-06-08 Revised:2020-07-30 Published:2021-08-19

摘要: 为了得到稳定有序的道路交通流,针对高速公路系统,提出了一种基于改进宏观交通流模型的模型预测控制方法。考虑到由于匝道的流入和流出给交通流带来的不确定性,该方法以各路段的交通流密度和速度为控制目标。再以传统的宏观交通流模型为基础,改进得到一个宏观交通流状态空间模型。针对多变量和控制量约束的问题,设计了基于模型预测控制的交通流密度和速度控制器,以保证更好的控制效果。仿真结果表明,交通流的密度和速度最终趋于期望值,即该方法可有效避免交通拥堵。

关键词: 高速公路系统, 模型预测控制, 交通流密度和速度控制, 宏观交通流模型

Abstract: In order to obtain stable and orderly traffic flow, a model predictive control method based on improved macroscopic traffic flow model is proposed for highway system. Considering the uncertainty caused by the inflow and outflow of ramp, the method takes the traffic density and velocity of each section as the control target. Based on the traditional macroscopic traffic flow model, a macroscopic traffic flow state space model is improved. Aiming at the problem of multiple variables and control constraints, a traffic flow density and velocity controller based on model predictive control is designed to ensure better control effect. The simulation results show that the density and velocity of traffic flow eventually converge to the expected value, and the method can effectively avoid traffic congestion.

Key words: highway system, model predictive control, traffic flow density and velocity control, macroscopic traffic model

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