基于模型预测的快速交通网络路由诱导方法

为了达到均衡城市快速路网交通负荷,提高交通运行效率的目的,提出了模型预测路由诱导控制方法,控制任务描述为一个动态的、离散时间、空间的、带有约束控制变量的最优控制问题.采用宏观、确定型的、离散时间、空间、适合基于模型预测交通控制的宏观动态交通模型来构建网络交通过程模型,通过在未来较长的时段内求解每一个控制周期的最优问题来实现反馈控制.仿真实例研究结果表明,模型预测路由诱导控制方法能够考虑时变的交通状态,取得良好的控制效果,可为先进的交通管理系统构建提供依据.

Model-based Predictive Route Guidance Method for Urban Freeway Network

In order to equilibrate traffic flow on urban expressway network,and improve the efficiency of traffic operation,the paper proposes an feedback optimal control model for urban freeway by using Model-based Predictive Control (MPC) framework.The control task is formulated as a dynamic,nonlinear,discrete time optimal control problem with constrained control variables.The network traffic process is modeled by a macroscopic network traffic flow model,which is deterministic,discrete time,discrete space,and macroscopic and suitable for model based traffic control.Feedback control is realized by solving the optimization problem for each control interval over a sufficiently long future time horizon.Simulation results for a case study show that with the proposed MPC traffic control,the time-dependent traffic characteristics can be accounted for;a high degree of control benefits can be guaranteed,and reference for ATMS is provided.