论文标题
使用一阶宏观交通流量模型进行稳健的交通控制
Robust Traffic Control Using a First Order Macroscopic Traffic Flow Model
论文作者
论文摘要
交通管制是运输工程研究的核心，因为它是减少交通拥堵的最佳实践之一。近年来已经表明，涉及Lighthill-Whitham-Richards（LWR）模型的交通控制问题可以作为线性编程（LP）问题提出，鉴于基本图中相应的初始条件和模型参数是固定的。但是，在研究实际的控制问题时，初始条件可能不确定。本文提出了涉及机会限制的边界控制问题的随机编程公式，以捕获初始条件下的不确定性。使用此框架探索了不同的目标功能，并为单个高速公路链接和小型网络进行了案例研究。此外，使用蒙特卡洛模拟验证了最佳结果。
Traffic control is at the core of research in transportation engineering because it is one of the best practices for reducing traffic congestion. It has been shown in recent years that the traffic control problem involving Lighthill-Whitham-Richards (LWR) model can be formulated as a Linear Programming (LP) problem given that the corresponding initial conditions and the model parameters in the fundamental diagram are fixed. However, the initial conditions can be uncertain when studying actual control problems. This paper presents a stochastic programming formulation of the boundary control problem involving chance constraints, to capture the uncertainty in the initial conditions. Different objective functions are explored using this framework, and case studies for both a single highway link and a small network are conducted. In addition, the optimal results are validated with Monte Carlo simulation.
