Driving intent recognition is essential to ensure traffic safety and improve traffic efficiency.In order to realize the prediction of future vehicle driving intention,based on the trajectory prediction and driving intention recognition method,this study selects the Argoverse public dataset as the training and test dataset,and proposes a driving intention recognition method combining VectorNet trajectory prediction model and random forest classification model to realize the driving intention recognition for the future 3s.In order to verify the effectiveness of the proposed method,the newly proposed VectorNet-random forest model is compared with the LSTM-random forest model,and the results show that the proposed method has better results.This method provides a reference for the development of autonomous driving and intelligent transportation systems in the future.
维普
万方数据