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A multi-class model-based control scheme for reducing congestion and emissions in freeway networks by combining ramp metering and route guidance

机译:一种基于模型的多类控制方案,通过结合匝道计量和路线引导来减少高速公路网络中的拥堵和排放

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The paper proposes a multi-class control scheme for freeway traffic networks. This control scheme combines two control strategies, i.e. ramp metering and route guidance, in order to reduce the total time spent and the total emissions in a balanced way. In particular, the ramp metering and route guidance controllers are feedback predictive controllers, i.e. they compute the control actions not only on the basis of the measured system state, but also on the basis of the prediction of the system evolution, in terms of traffic conditions and traffic emissions. Another important feature of the controllers is that they have a multi-class nature: different classes of vehicles are considered and specific control actions are computed for each class. Since the controllers are based on a set of parameters that need to be tuned, the overall control framework also includes a module to properly determine the gains of the controllers. The simulation analysis reported in the paper shows the effectiveness of the proposed control framework and, in particular, the possibility of implementing control policies that are specific for each vehicle type. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文提出了一种高速公路交通网络的多类控制方案。该控制方案结合了两种控制策略,即坡道计量和路线引导,以便以平衡的方式减少花费的总时间和总排放量。特别地,坡道计量和路线引导控制器是反馈预测控制器,即,它们不仅基于所测量的系统状态来计算控制动作,而且还基于交通状况来计算系统演化的预测来计算控制动作。和交通排放。控制器的另一个重要特征是它们具有多类别的性质:考虑不同类别的车辆,并针对每个类别计算特定的控制动作。由于控制器基于一组需要调整的参数,因此总体控制框架还包括一个模块,可正确确定控制器的增益。本文中报告的仿真分析显示了所提出的控制框架的有效性,尤其是实施针对每种车辆类型的控制策略的可能性。 (C)2017 Elsevier Ltd.保留所有权利。

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