基于雾计算和强化学习的交通灯智能协同控制研究

被引：7

作者：

安萌萌

樊秀梅

蔡含宇

机构：

[1] 西安理工大学自动化与信息工程学院

来源：

计算机应用研究 | 2020年 / 37卷 / 02期

关键词：

十字路口; 交通灯; 雾计算; 强化学习; Q学习;

D O I：

10.19734/j.issn.1001-3695.2018.08.0543

中图分类号：

U491.54 []; TP181 [自动推理、机器学习];

学科分类号：

0838 ;

摘要：

针对路口交通拥堵现象,结合雾计算和强化学习理论,提出了一种FRTL(fog reinforcement traffic light)交通灯控制模型,该模型根据实时的交通流信息进行交通灯智能协同控制。雾节点将收集到的实时交通流信息上传到雾服务器,雾服务器在雾平台实现信息共享,雾平台结合处理后的共享数据和Q学习制定交通灯控制算法。算法利用检测到的实时交通数据计算出合适的交通灯配时方案,最终应用到交通灯上。仿真结果表明,与传统的分时段控制方式和主干道控制方式(ATL)相比,FRTL控制方法提高了路口的吞吐量,减少了车辆平均等待时间,达到了合理调控红绿灯时间、缓解交通拥堵的目标。

引用

页码：465 / 469

页数：5

共 49 条

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