Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks
Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale …