The invention discloses a ramp control method for solving the congestion problem of a bottleneck section of an expressway. The method comprises the following steps of (1) determining the bottleneck section of the expressway, and arranging a coil detector, (2) setting signal lamps at the entrance and exit of the ramp, and calculating a Q value through receiving a state set and an action set by deep reinforcement learning, (3) constructing a simulation road network by applying an SUMO simulation platform, (4) determining three indexes of deep reinforcement learning, namely a state set, an action set and a return function, and formulating a control strategy, (5) enabling the intelligent agent to execute the signal lamp, and (6) calling a TraCI interface of the SUMO simulation platform by utilizing a Python language to start simulation, then acquiring data in simulation in real time by utilizing statements, extracting useful information, calculating a control strategy, obtaining a corresponding control strategy result, and then calling the TraCI interface to set the color of a signal lamp in simulation so as to realize the application of the control strategy.
本发明公开了一种解决快速道路瓶颈路段拥堵问题的匝道控制方法,包括如下步骤:步骤(1)确定快速道路瓶颈路段,安置线圈检测器;步骤(2)在匝道进出口处设置信号灯,深度强化学习通过接收状态集和动作集,计算出Q值;步骤(3)应用SUMO仿真平台进行仿真路网的搭建:步骤(4)确定深度强化学习的三个指标,状态集、动作集、回报函数,制定控制策略;步骤(5)智能体执行信号灯;步骤(6)利用Python语言调用SUMO仿真平台的TraCI接口启动仿真,随后利用语句实时获取仿真中的数据,提取有用信息,进行控制策略的计算,得出相应的控制策略结果后,再调用TraCI接口设置仿真中的信号灯灯色以实现控制策略的应用。
Ramp control method for solving congestion problem of bottleneck section of expressway
一种解决快速道路瓶颈路段拥堵问题的匝道控制方法
2021-11-19
Patent
Electronic Resource
Chinese
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