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Model predictive control of large-scale urban networks via perimeter control and route guidance actuation

机译:通过周边控制和路线引导致动对大型城市网络进行模型预测控制

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We design model predictive control (MPC) schemes to improve urban mobility in heterogeneously congested large-scale traffic networks, the modeling and control of which remains a challenge. The multi-region urban network is modeled using the macroscopic fundamental diagram (MFD) of urban traffic, with each region having a well-defined MFD. For more realistic simulations of urban networks with route guidance actuation based control, we propose a new model with cyclic behavior prohibition. Furthermore, we extend upon earlier work on perimeter control based MPC schemes with MFD modeling by integrating route guidance type actuation, which distributes flows exiting a region over its neighboring regions. Performance of the proposed schemes are evaluated via simulations of a congested scenario with noise in demand estimation and measurement errors. Results show the possibility of substantial improvements in urban network performance.
机译:我们设计了模型预测控制(MPC)方案,以提高异构拥挤的大规模交通网络中的城市交通,其建模和控制仍然是一个挑战。使用城市交通的宏观基本图(MFD)对多区域城市网络进行建模,每个区域都具有定义明确的MFD。为了更实际地模拟基于路线引导致动的城市网络,我们提出了一种具有循环行为禁止的新模型。此外,我们通过集成路线引导类型的致动来扩展基于MFD建模的基于边界控制的MPC方案的早期工作,该路线引导类型的致动将离开某个区域的流量分配到其相邻区域。拟议方案的性能是通过模拟拥塞情况进行评估的,该拥堵情况在需求估计和测量误差中带有噪声。结果表明,可能会大幅改善城市网络的性能。

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