The invention belongs to the field of intelligent traffic, and discloses an expressway tunnel vehicle lane change guiding method based on a travel time prediction model, which comprises the following steps: S1, acquiring trajectory data of an intelligent network connection vehicle in a tunnel, and preprocessing the trajectory data; s2, carrying out correlation analysis on the travel time characteristics, extracting the travel time characteristics by taking Tpre seconds as a detection period, carrying out normalization processing on data, and constructing a travel time prediction data set; s3, building a travel time prediction model of PSO-CNN-LSTM-AM, inputting a travel time prediction data set into the model for training, and then performing experimental comparison and verification; and S4, performing periodic prediction by using the model trained in the step S3, and proposing a lane change control method for an expressway tunnel entrance area based on a travel time prediction value. According to the method, important features can be better extracted, a more accurate prediction effect is achieved, the tunnel double-lane utilization rate and the traffic efficiency can be improved, and traffic congestion is relieved.
本发明属于智能交通领域,公开了一种基于行程时间预测模型的高速公路隧道车辆换道引导方法,包括:S1.获取隧道内智能网联汽车的轨迹数据,并对轨迹数据进行预处理;S2.对行程时间特征进行相关性分析,以Tpre秒为检测周期提取行程时间特征,对数据进行归一化处理,构建行程时间预测数据集;S3.搭建PSO‑CNN‑LSTM‑AM的行程时间预测模型,将行程时间预测数据集输入到模型中进行训练,然后进行实验对比与验证;S4.利用步骤S3训练好的模型进行周期性预测,基于行程时间预测值,提出高速公路隧道入口区换道控制方法。本发明能够更好的提取重要特征,实现更精确的预测效果,能够提高隧道双车道利用率以及交通效率,缓解交通拥堵。
Expressway tunnel vehicle lane change guiding method based on travel time prediction model
一种基于行程时间预测模型的高速公路隧道车辆换道引导方法
2024-09-17
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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