Systematic experiments on four traffic datasets find that a 1-block STGCN achieves optimal short-term (10 min) prediction on three datasets with only marginal longer-horizon degradation and 61% lower CPU latency than the standard 2-block model.
Do we really need graph neural networks for traffic forecasting?
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Efficient Traffic Prediction at Scale: A Systematic Study of STGCN Architectural Depth
Systematic experiments on four traffic datasets find that a 1-block STGCN achieves optimal short-term (10 min) prediction on three datasets with only marginal longer-horizon degradation and 61% lower CPU latency than the standard 2-block model.