GCN model combined with Bi-GRU for traffic prediction

The acceleration of the urbanization process puts a higher demand on traffic management. In the last few years, ITS(intelligent transportation systems) have played a significant role, and traffic prediction is an important content among them. In fact, traffic forecasting is very challenging, mainly due to the temporal-spatial nature of the related traffic data. For this article, we propose an optimization method of graph convolutional neural network with Bi-GRU to optimize traffic prediction. Experiments show that our model has achieved good results and provides a new perspective for studying such problems.