基于MPC的快速路协同控制策略研究

发布时间：2018-03-16 04:31

本文选题：快速路　切入点：协同控制策略　出处：《哈尔滨工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：组合两种或多种控制策略对快速路进行协同控制,能够有效缓解交通拥堵,保证交通流安全、稳定地运行。然而,已有研究尚未系统地分析协同控制的影响因素,未能深入比较与分析基于不同交通流模型的协同控制策略,此外,经典宏观交通流模型以及相关控制算法也有待完善。针对上述问题,论文从机理、技术、应用以及效果四个方面开展快速路协同控制策略研究。论文分析了快速路的主要交通特征,阐述了快速路交通流的恶化过程,指出协同控制是避免交通流突变的有效手段,并采用文献综述法和机理分析法从理论方法、技术应用以及外部环境这三个方面系统分析了协同控制的影响因素。对匝道控制和可变限速控制相关算法分别展开研究,改进了PI-ALINEA算法,提出实现目标密度自动更新的自适应匝道控制系统;从实时更新预设密度、考虑车辆遵守率以及实现主动式控制等三方面完善了MTFC-VSL算法。在此基础上,构建了基于MPC的快速路协同控制框架,并设计了多目标遗传算法实现控制策略优化求解。分别考虑入口匝道控制和可变限速控制的影响,修正了METANET和CTM两种宏观交通流模型,并设计了模型标定与验证方法。将改进模型与协同控制框架相结合,提出了基于不同交通流模型的MPC协同控制策略。针对两种控制策略进行了仿真实验,共设置四种控制场景:无控制、入口匝道控制、可变限速控制以及协同控制,从交通效率和交通安全两方面对比了各控制场景下两种控制策略的异同。结果显示,两种交通流模型均能较好模拟实际道路交通流运行,基于METANET的MPC协同控制策略控制效益更优。
[Abstract]:The combination of two or more control strategies can effectively alleviate traffic congestion, ensure traffic flow safety and stable operation. However, the influence factors of collaborative control have not been systematically analyzed. The cooperative control strategies based on different traffic flow models have not been thoroughly compared and analyzed. In addition, the classical macro-traffic flow model and related control algorithms need to be improved. This paper analyzes the main traffic characteristics of expressway, expounds the deterioration process of expressway traffic flow, and points out that collaborative control is an effective means to avoid the sudden change of traffic flow. The paper also systematically analyzes the influence factors of cooperative control from three aspects: theoretical method, technical application and external environment by using literature review method and mechanism analysis method. The related algorithms of ramp control and variable speed limit control are studied respectively. The PI-ALINEA algorithm is improved, and an adaptive ramp control system for automatic updating of target density is proposed, and the MTFC-VSL algorithm is improved from three aspects: real-time updating of preset density, consideration of vehicle compliance rate and realization of active control. In this paper, a framework of expressway cooperative control based on MPC is constructed, and a multi-objective genetic algorithm is designed to optimize the solution of control strategy. Considering the influence of on-ramp control and variable speed limit control, two macroscopic traffic flow models, METANET and CTM, are modified. Combining the improved model with the collaborative control framework, the MPC collaborative control strategy based on different traffic flow models is proposed. The simulation experiments are carried out for two control strategies. There are four control scenarios: no control, on-ramp control, variable speed limit control and collaborative control. The similarities and differences between the two control strategies are compared in terms of traffic efficiency and traffic safety. The two traffic flow models can well simulate the actual traffic flow, and the control efficiency of MPC cooperative control strategy based on METANET is better.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491

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