STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction

arXiv:2209.00225v2 Announce Type: replace
Abstract: High-performance traffic flow prediction model designing, a core technology of Intelligent Transportation System, is a long-standing but still challenging task for industrial and academic communities. The lack of integration between physical principles and data-driven models is an important reason for limiting the development of this field. In the literature, physics-based methods can usually provide a clear interpretation of the dynamic process of traffic flow systems but are with limited accuracy, while data-driven methods, especially deep …

abstract academic arxiv communities core cs.lg data data-driven designing development flow industrial integration intelligent intelligent transportation networks neural networks performance physics prediction reason technology traffic transportation type