基于ACP的城市交叉口自学习控制

Feng Chen, Lingyun Zhu, C. Han, Xiong Gang
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引用次数: 0

摘要

延误模型和排队长度模型等交叉口模型是城市交叉口信号配时优化的基础。由于缺乏交叉口现场数据,交叉口模型参数的标定非常困难。由于交叉口拓扑、通道化和交通条件对这些模型的影响,显然单一模型不可能适用于多个交叉口的最优控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ACP based self-learning control for urban intersection
The intersection models, such as delay models and queuing length models, are the foundations of optimal signal timing for urban intersection. Lack of the field data of intersection, it is highly difficult to calibrate parameters of the intersection models. Due to the effects of intersection topology, channelization and traffic conditions on these models, obviously it is impossible for single model to be suitable for optimal control of various intersections.
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