Research on pedestrian trajectory prediction method based on social attention mechanism - Linhui LI; Bin ZHOU; Jing LIAN; Yafu ZHOU (Tongxin xuebao)
In order to improve the speed,accuracy and model interpretability of trajectory prediction in pedestrian interaction,a GAN model based on social attention mechanism was proposed.Firstly,a new type of social relationship on pedestrians was defined to model social relationships and a network model based on the attention mechanism was designed to improve the speed and interpretability of network prediction.Secondly,the influence of different pooling mechanisms on the prediction results was explored to determine the pooling model with excellent performance.Finally,a trajectory prediction network was built on this basis and trained on the UCY and ETH data sets.The experimental results show that the model not only has better prediction accuracy than the existing methods,but also improves the real-time performance by 18.3% compared with the existing methods.