系统仿真学报 ›› 2020, Vol. 32 ›› Issue (2): 149-156.doi: 10.16182/j.issn1004731x.joss.19-0675

• 专栏:交通仿真 •    下一篇

降雨情景下城市道路交通信号控制优化模型与方法

唐少虎1, 周进1*, 尚春琳2, 郑国荣2   

  1. 1. 北京联合大学,北京 100101;
    2. 北方工业大学,北京 100144
  • 收稿日期:2019-12-24 修回日期:2019-12-27 出版日期:2020-02-18 发布日期:2020-02-19
  • 作者简介:唐少虎(1986-),男,山东,博士,讲师,研究方向为城市交通管理与控制;周进(通讯作者1970-),女,江苏,硕士,副教授,研究方向为交通工程。
  • 基金资助:
    国家重点研发计划(2018YFC0809900),北京市自然科学基金(8184070),“天诚汇智”创新促教基金(2018A01012)

Optimization Model and Method of Urban Road Traffic Signal Control under Rainfall Environment

Tang Shaohu1, Zhou Jin1*, Shang Chunlin2, Zheng Guorong2   

  1. 1. Beijing Union University, Beijing 100101, China;
    2. North China University of Technology, Beijing 100144, China
  • Received:2019-12-24 Revised:2019-12-27 Online:2020-02-18 Published:2020-02-19

摘要: 降雨天气导致城市道路交通运行效率明显下降,现有道路交通信号控制一般尚未建立针对性的信号优化方案。考虑降雨天气降水量、道路积水等因素影响下的交通运行情景,设计了面向交通控制的城市道路交通信息物理系统体系,搭建了基于信息物理系统的城市道路交通控制框架,并建立了交通信号控制优化模型,进一步利用BP神经网络方法设计了模型求解方法。通过搭建实例路口交通仿真模型,对比3种方案下延误时间等多个指标,分析结果表明本文方法在改善降雨情景下交叉口交通运行效率等方面的有效性。

关键词: 降雨情景, 交通信号控制, 信息物理系统, BP神经网络

Abstract: The efficiency of urban road traffic operation fell obviously during a rain, and the existing road traffic signal control has not yet established a relevant signal optimization scheme. Considering the traffic operation scenario under the influence of rainfall and road water, an urban road traffic cyber physical systems is designed, a framework of urban road traffic control based on cyber physical systems is built, an optimization model of traffic signal control is established, and further more, the solution method of the model is designed by using BP neural network. Building a traffic simulation model of the example intersection, comparing the delay time and other indicators under the three schemes, the analysis results proved the effectiveness of this method in improving the traffic operation efficiency of the intersection under the rainfall scenario.

Key words: rainfall scenario, traffic signal control, cyber physical system, BP neural network

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