基于分布式模型预测控制的城市快速路多匝道协同控制
Coordinated Ramp Metering for Urban Expressway Based on Distributed Model Predictive Control
摘要: 模型预测控制(Model Predictive Control, MPC)是一种适用于多匝道协同控制的控制策略，但其因计算时间过长而难以在复杂路网中实时实施。为了减少MPC控制复杂路网的计算时间，采用分布式控制思想，考虑交通流的单向性，提出一种贯序分布式多匝道MPC控制方案，各控制器依次根据上游控制器传递的交通信息确定最优匝道控制率。最优控制模型采用METANET交通流模型作为过程模型，综合考虑通行效率、匝道队列和控制信号波动构建目标函数，通过求解目标函数在线优化问题得到最佳的入口匝道控制率。仿真结果表明，相较于集中式MPC控制和分散式MPC控制，所提出的贯序分布式多匝道MPC控制方案可以在提高路网表现和降低计算复杂度间达到平衡。
Abstract: Model Predictive Control (MPC) is a control strategy suitable for cooperative control of multiple ramps, but it is difficult to implement in real time in complex road networks due to the long com-putational time. In order to reduce the computational time for MPC control of complex road net-works, a sequential distributed multi-ramp MPC control scheme was proposed, taking into account the unidirectional nature of traffic flow, where each controller determined the optimal ramp me-tering rate in turn based on the traffic information transmitted by the upstream controller. METANET traffic flow model was adopted as the process model, and the objective function was con-structed by considering traffic efficiency, ramp queue and control signal fluctuation. The simulation results showed that the proposed sequential distributed MPC ramp metering strategy offered a trade-off between computational complexity and system performance compared to the centralized MPC strategy and decentralized MPC strategy.
文章引用：杨雪驰. 基于分布式模型预测控制的城市快速路多匝道协同控制[J]. 建模与仿真, 2023, 12(4): 3550-3563. https://doi.org/10.12677/MOS.2023.124327

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