The invention provides an expressway risk prediction method based on LSTM and BF. The expressway risk prediction method comprises offline risk early warning prediction model training and online risk early warning model real-time prediction. Offline risk early warning prediction model training comprises the steps of constructing an LSTM instantaneous risk discrimination model for distinguishing an accident from a safety state, and establishing a BF sequence risk prediction model based on a decline coefficient, a prior probability and a threshold value; and during the online risk early warning model real-time prediction, an output sequence of the LSTM instantaneous risk discrimination model on each observation point in a specified period is taken as an input vector, an observation frequency proportion in the mode is taken as a prior probability, the input vector is input into the BF sequence risk prediction model, and finally a future road section risk state prediction result is obtained. According to the invention, the precision of highway real-time risk prediction is improved.
本发明提供了一种基于LSTM和BF的高速公路风险预测方法,包括线下风险预警预测模型训练和线上风险预警模型实时预测;线下风险预警预测模型训练包括构建区分事故与安全状态的LSTM瞬时风险判别模型,以及建立基于递减系数、先验概率和阈值的BF序列风险预测模型;线上风险预警模型实时预测时,以规定周期内各观测点上LSTM瞬时风险判别模型的输出序列为输入向量,以模式内的观测频数占比为先验概率,输入BF序列风险预测模型,最终得到未来路段风险状态预测结果。本发明提高了高速公路实时风险预测的精度。
Expressway risk prediction method based on LSTM and BF
一种基于LSTM和BF的高速公路风险预测方法
2021-12-03
Patent
Electronic Resource
Chinese
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