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The iterative learning approach for vehicle queuing length balanced-control of the signalized isolated intersection

机译:信号隔离交叉口车辆排队长度均衡控制的迭代学习方法

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In this work, the iterative learning control approach is proposed to address the signalized isolated intersection control problem. The signal timing should be adjusted according to the real-time daily-repeated traffic demand to ensure the full utilization of green time. However, it is difficult to establish the exact mathematic model of isolated intersection with the time-varying demand. The iterative learning control approach requires much less system modeling knowledge and also rejects the exogenous traffic perturbations. Rigorous analyses show that the proposed learning control scheme can guarantee the convergence of the vehicle queuing length difference to the desired one. The effectiveness of the proposed approach is also verified through simulations.
机译:在这项工作中,提出了迭代学习控制方法来解决信号隔离路口控制问题。信号定时应根据每天重复的实时流量需求进行调整,以确保充分利用绿色时间。但是,很难建立具有时变需求的精确交叉口数学模型。迭代学习控制方法所需的系统建模知识少得多,并且还拒绝了外部流量干扰。严格的分析表明,所提出的学习控制方案可以保证车辆排队长度差收敛到期望值。通过仿真也验证了所提方法的有效性。

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