关键词: 轨迹预测, 生成对抗网络, 注意力机制

Abstract:

In order to predict the trajectory of pedestrians in complex scenes, an interpretable model based on generative adversarial networks is proposed. The model takes the historical trajectory information of the pedestrians in the scene and the environment information of the scene as the input of the model, and introduces physical attention mechanism and social attention mechanism into the generative adversarial network to predict the pedestrian trajectory. Among them, the physical attention mechanism helps to model the overall layout of complex scenes and extract significant features related to paths in the image. The social attention mechanism can model the impact of different pedestrian interactions on future trajectories. Under the overall framework of generative adversarial networks, the combination of physical and social attention mechanisms enables the model to predict multiple acceptable future paths that meet physical constraints and social behavior norms. Experiments on simulation data and real standard datasets prove the model can effectively predict the future trajectory of pedestrians.

Key words: trajectory prediction, generative adversarial network, attention mechanism