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Model Free Adaptive Perimeter Control for Two-Region Urban Traffic System with Input and Output Constraints

机译:具有输入和输出约束的两区域城市交通系统的无​​模型自适应边界控制

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Recent studies on urban traffic systems have shown that there exists a well-defined macroscopic fundamental diagram (MFD) in well-partitioned homogenous regions, which depicts a unimodal and low-scatter relationship between accumulation and trip completion flow. In this paper, a new type of data driven control method called model free adaptive control with input and output constraints (IOC-MFAC) is utilized for perimeter control for two-region urban traffic system, using MFD to choose the desired number of vehicles and generate the output data of the urban traffic system. Different from the protype scheme of MFAC, in this work, the constraints of perimeter control input and the urban traffic system's output are considered. A key advantage of the proposed method is that only the input and output data of the urban traffic system is needed to design the perimeter controller. The effectiveness of IOC-MFAC method is tested via numerical simulation, and the result shows that it works better than some other commonly used perimeter control strategies.
机译:最近对城市交通系统的研究表明,在划分合理的同质区域中存在一个定义明确的宏观基本图(MFD),该图描述了累积量与出行完成流量之间的单峰和低散度关系。在本文中,一种新型的数据驱动控制方法称为带有输入和输出约束的无模型自适应控制(IOC-MFAC),用于两区域城市交通系统的周边控制,使用MFD选择所需的车辆数量和生成城市交通系统的输出数据。与MFAC的原型设计方案不同,在这项工作中,考虑了边界控制输入和城市交通系统输出的约束。该方法的关键优势在于,仅需要城市交通系统的输入和输出数据即可设计周边控制器。通过数值模拟测试了IOC-MFAC方法的有效性,结果表明该方法比其他一些常用的边界控制策略更好。

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