城市交通的分层反馈控制

发布时间：2023-10-14 08:10

　　城市交通日益拥堵,引发了污染、不安全以及通勤时间延长等一系列问题,给社会经济带来不利影响。由于土地使用限制和环境限制,持续增加基础设施建设已不能作为解决城市交通拥堵问题的方法,而是需要通过一系列的交通控制措施,最优利用现有的基础设施。本文将十字路口的交通灯作为控制器件,优化红绿灯的转换时间可以使得城市区域内所有车辆的总通行时间达到最少。对于一个城市区域内的交通,反馈控制问题的复杂性要求对其基于不同的抽象级别分层地进行求解。本文提出,基于模型的局部反馈控制器使用详细的交通模型,在低层以较快的时间尺度选择每一个十字路口的交通灯的转换时间,从而优化这一区域内的交通流,而边界控制在高层使用更加聚合的交通数据,以较慢的时间尺度来确定进入这一区域的车流速度,从而避免该区域拥堵。基于模型的交通反应式策略已经被提出了很长时间。最初,这些策略使用的模型是一些简单的交通流预测模型,其主要是基于感应线圈检测器测量的交通数据,而感应线圈检测器通常位于十字路口车辆停止线上游40米处。从那时起,基于详细的交通流动态预测模型,许多方法相继被提出,并采用各种数值求解算法,包括混合整数线性规划、遗传算法和粒子群算法。然...

【文章页数】：161 页

【学位级别】：博士

【文章目录】：
摘要
ABSTRACT
List of Symbols
List of Abbreviations
Chapter 1 Introduction
    1.1 Overview of control of urban traffic
    1.2 Motivation and contributions
    1.3 Dissertation structure
Chapter 2 Preliminary
    2.1 Traffic flow theory
        2.1.1 Time-space diagram
        2.1.2 Cumulative plots
        2.1.3 Measurement interval
        2.1.4 Density, flow and space-mean speed
        2.1.5 Conservation law and fundamental diagram
    2.2 Control methodology
        2.2.1 Elements of control design
        2.2.2 Single-agent model Predictive Control
        2.2.3 Multi-agent model predictive control
    2.3 Summary
Chapter 3 Urban Cell Transmission Model
    3.1 Motivation
    3.2 Components of network
        3.2.1 Region
        3.2.2 Intersections
        3.2.3 Sinks and sources
        3.2.4 Traffic load at intersections
        3.2.5 Links and cells
    3.3 Dynamic behaviour of traffic
        3.3.1 UCTM dynamic link model
        3.3.2 Merge and diverge constraints
        3.3.3 Representation of randomness in traffic behaviour
    3.4 Performance evaluation using UCTM
        3.4.1 Delay in UCTM
        3.4.2 Queues in UCTM
    3.5 Validation of UCTM
        3.5.1 Simulation implementation
        3.5.2 Case study
        3.5.3 Validation of aggregated behaviour
        3.5.4 Validation of state trajectories of cells in different cases
    3.6 Summary
Chapter 4 Local and Coordinated Model Predictive Controllers
    4.1 Introduction
    4.2 Local MPC
        4.2.1 Local information needed by Agenti
        4.2.2 Choice of scenarios for Agenti
        4.2.3 Objective function of local agent
        4.2.4 Optimization via simulation
    4.3 Performance evaluation of Local MPC
        4.3.1 Case study
        4.3.2 Design of controllers for comparison to local MPC
        4.3.3 Performance analysis
    4.4 Coordinated MPC
        4.4.1 Scenarios
        4.4.2 Information needed by Agenti
        4.4.3 Cost function of Agenti
        4.4.4 Optimization via simulation
    4.5 Performance evaluation of coordinated MPC
        4.5.1 Simulation settings
        4.5.2 Performance analysis
        4.5.3 Green waves generation in a simple case
    4.6 Summary
Chapter 5 Stability Enhancement and Hierarchical Feedback Control
    5.1 Motivation
    5.2 Coordinated MPC with stabilization constraint
        5.2.1 Intuition about stability issues for coordinated MPC
        5.2.2 CMPC with stabilization constraint
        5.2.3 Implementation of CMPC with stabilization constraint
    5.3 Performance evaluation of coordinated MPC with stabilization constraint
        5.3.1 Detailed performance analysis of one simulations run
        5.3.2 Statistical analysis
    5.4 Hierarchical feedback control
        5.4.1 Macroscopic fundamental diagram
        5.4.2 Description of high-level controller
        5.4.3 Hierarchical control framework
    5.5 Summary
Chapter 6 Conclusions and Future Work
    6.1 Conclusions
    6.2 Future work
References
Acknowledgement
Biography



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