The invention aims to provide a traffic flow prediction method and equipment based on feature processing, so as to ensure the maximum traffic flow in a safe state as far as possible. In order to achieve the purpose, an LSTM model is established, the model inputs time sequence characteristics of a second timeline, and the LSTM model is adopted to carry out multivariate time sequence prediction; establishing a decision tree model based on optimized gradient lifting on the basis of multivariate time sequence prediction; and finally, establishing a prediction model of the spatio-temporal information and other related feature information. Calculating a predicted traffic flow on the second timeline by using a prediction model of the spatio-temporal information and other related feature information; and when the predicted traffic flow exceeds the safety expectation, pre-regulation management is carried out on the specified highway entrance and exit. Prediction is carried out through the method, the processing scheme is continuously optimized, and then the regulation and control strategy of the traffic flow of the expressway intersection is optimized.
本发明的目的是提供一种基于特征处理的交通流量预测方法及设备,从而尽可能实现保证安全状态下的最大车流量。为了实现上述目的,本发明建立LSTM模型,该模型输入为第二时间线的时序特征,采用LSTM模型进行多元时间序列预测;在多元时间序列预测基础上建立基于优化的梯度提升的决策树模型;最终建立时空信息与其他相关特征信息的预测模型;利用时空信息与其他相关特征信息的预测模型计算第二时间线上的预测车流量;当预测的车流量超过安全预期时对指定高速出入口进行预调控管理。通过本发明进行预测,不断优化处理方案,进而优化高速路口车流量的调控策略。
Traffic flow prediction method and device based on feature processing
一种基于特征处理的交通流量预测方法及设备
2022-12-02
Patent
Elektronische Ressource
Chinesisch
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