A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction. (arXiv:2305.07416v1 [cs.LG])

This work introduces the multidimensional Graph Fourier Transformation Neural
Network (GFTNN) for long-term trajectory predictions on highways. Similar to
Graph Neural Networks (GNNs), the GFTNN is a novel network architecture that
operates on graph structures. While several GNNs lack discriminative power due
to suboptimal aggregation schemes, the proposed model aggregates scenario
properties through a powerful operation: the multidimensional Graph Fourier
Transformation (GFT). The spatio-temporal vehicle interaction graph of a
scenario is converted into a spectral scenario representation using the GFT. …

aggregation architecture arxiv gnns graph graph neural networks long-term multidimensional network network architecture networks neural network neural networks novel power prediction predictions trajectory transformation work