Highway toll station congestion detection model and method based on scene image segmentation

The embodiment of the invention provides an expressway toll station congestion detection model and method based on scene image segmentation, and the method comprises the steps: inputting training samples into an expressway toll station congestion detection model for training, and inputting each training sample into a feature extraction module to extract video features at different time points; the video features at different time points are input into a time sequence feature reconstruction module to be reconstructed to obtain a feature matrix corresponding to the current training sample, and feature values in the feature matrix are target vehicle features combined with surrounding environment information; the feature matrix is input into a congestion state evaluation module, an unsupervised anomaly detection algorithm is used for evaluation to obtain a prediction result of a congestion state or a non-congestion state, and the unsupervised anomaly detection method is used for analyzing the feature matrix corre