Abstract: A method related to the field of environment modeling of traffic scenarios is disclosed. Specifically, a method for extracting features from data of a traffic scenario based on a graph neural network is disclosed. The method includes the following steps: step (S1): establishing uniformly defined data representations for the data of the traffic scenario; step (S2): constructing a graph based on the data of the traffic scenario that has the uniformly defined data representations, where the graph describes a temporal and/or spatial relationship between entities in the traffic scenario; and step (S3): using the constructed graph as an input of the graph neural network to perform learning on the graph neural network, such that the features are extracted from the data of the traffic scenario. A device for extracting features from data of a traffic scenario based on a graph neural network and a computer program product is also disclosed.