The invention provides a road traffic jam prediction method based on artificial intelligence, and the method comprises the steps: obtaining the positioning information and navigation information of a plurality of mobile terminals, and projecting the positioning information and navigation information into a multi-dimensional space coordinate system to generate a multi-dimensional space data point set; calculating the intensity of the mobile terminal according to the data point set, screening out first congestion information, and removing non-actual congestion data points caused by the state of the signal lamp to obtain second congestion information; drawing a traffic flow space curve and performing feature extraction to generate a feature vector; inputting the feature vector into a congestion mode classification model based on long and short term memory network training to generate a traffic congestion mode; and predicting the time for the vehicle to pass the congested road section according to the congestion mode. According to the invention, by acquiring and analyzing the positioning information and the navigation information of the plurality of mobile terminals and combining the multi-dimensional spatial data point set and the LSTM model, the traffic flow and the congestion mode of different lanes can be accurately predicted.
本发明提供了一种基于人工智能的公路交通拥堵预测方法,包括获取多个移动终端的定位信息和导航信息,将其投射到多维空间坐标系中生成多维空间数据点集合;根据数据点集合计算移动终端的密集度,筛选出第一拥堵信息并剔除信号灯状态导致的非实际拥堵数据点,得到第二拥堵信息;绘制交通流量空间曲线并进行特征提取,生成特征向量;将特征向量输入到基于长短期记忆网络训练的拥堵模式分类模型中,生成交通拥堵模式;根据拥堵模式预测车辆通过拥堵路段的时间。本发明通过获取并分析多个移动终端的定位信息和导航信息,结合多维空间数据点集合和LSTM模型,可以精确预测不同车道的交通流量和拥堵模式。
Road traffic jam prediction method based on artificial intelligence
一种基于人工智能的公路交通拥堵预测方法
2024-08-23
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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