The invention relates to a tunnel lighting aid decision-making method based on traffic flow prediction, which aims at complex feature extraction hidden in traffic flow time sequence data, and comprises the following steps of: extracting short-term dependency features, time-dependent features and long-term dependency features by respectively utilizing Seq2Seq, Embedding and CNN for feature extraction, and performing feature fusion to obtain a final predicted traffic flow; the predicted traffic flow data of the tunnel in the future several hours, the infrared camera detection result and the tunnel interior position detection result are used as input parameters of an illumination system, an invalid illumination time period is obtained, and a corresponding illumination strategy is formulated. According to the method, prediction of future tunnel traffic flow is carried out by using deep learning and fusing multiple network models, and the prediction result is used as an auxiliary parameter for time-sharing control of a tunnel lighting system so as to be used in a tunnel ineffective lighting period; wherein the prediction network model considers short-term features, multiple periodic features and time-related factors in the traffic flow data, and the prediction precision is improved.

    本发明涉及一种基于车流量预测的隧道照明辅助决策方法,针对车流量时间序列数据中隐藏的复杂特征提取,特征提取分别利用Seq2Seq、Embedding、CNN提取短期依赖特征、时间相关特征、长期依赖特征,并进行特征融合,得到最终的预测车流量;进而利用预测的隧道未来几个小时的车流量数据、红外摄像检测和隧道内位置检测结果作为照明系统的输入参数,得到无效照明时段,制定相应的照明策略。本发明利用深度学习融合多种网络模型对未来隧道车流量的预测,并将预测结果作为辅助参数用于隧道照明系统的分时控制,以在隧道无效照明时段;其中预测网络模型考虑了车流量数据中的短期特征、多重周期特征和时间相关因素,预测精度提高。


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    Titel :

    Tunnel lighting auxiliary decision-making method based on traffic flow prediction


    Weitere Titelangaben:

    一种基于车流量预测的隧道照明辅助决策方法


    Beteiligte:
    DU ZHIQIANG (Autor:in) / ZHAO BEN (Autor:in) / GUO HANTIAN (Autor:in) / CAO JIENING (Autor:in)

    Erscheinungsdatum :

    2024-04-19


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / H05B ELECTRIC HEATING , Elektrische Heizung



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