Multi-modal trajectory prediction method for pedestrians in complex scene

The invention discloses a multi-modal trajectory prediction method for pedestrians in a complex scene. The method comprises the following steps: performing picture feature extraction by using a 16-layer convolutional neural network of a visual geometry group; performing feature processing on the trajectory data by using a full connection layer; inputting a trajectory data feature vector VS to enter a generative adversarial network to complete a coding and decoding network function; inputting picture feature data and track feature data to physics, wherein a social attention module considers terrain limitation and pedestrian interaction; obtaining a better track generation prediction result through the updated generator part; and obtaining a stable trajectory prediction model SPM. Accordingto the method, the prediction precision can be effectively improved, a plurality of reasonable prediction tracks can be generated, the related terrain limitation information can be extracted accordingto the feature informatio