SUBWAY PEDESTRIAN FLOW NETWORK FUSION METHOD BASED ON VIDEO PEDESTRIAN RECOGNITION, AND PEDESTRIAN FLOW PREDICTION METHOD

A subway pedestrian flow network fusion method based on video pedestrian recognition and a pedestrian flow prediction method. Video data of subway stations is used for performing statistical analysis on specific directions of the pedestrian flows entering and exiting the subway stations, the movement of crowds is performed in a huge network by means of fusing a subway network and a ground traffic network, each subway station is a node in the network, and each subway line and each on-ground road traffic line are sides of the network. A graph neural network is used for deducing the changes of the pedestrian flow of the whole traffic network so as to analyze and predict the pedestrian flow amount and the direction of the pedestrian flows at each station. Deeper pedestrian flow analysis for entrances of each subway station is achieved, the resource scheduling of each station and each entrance is facilitated, and the mutual influence of the on-ground pedestrian flow and the underground pedestrian flow can be pre-d