Layered diagnostic study finds better traffic forecasts do not necessarily improve signal control
This arXiv preprint presents a layered diagnostic framework using 29 days of reconstructed demand from Xuancheng, China, to trace why improved entry- and movement-level forecasts (≈4% MAE reduction) and calibrated conformal intervals often fail to yield better closed-loop signal-control decisions. The authors identify interface leakage, limited effective action choices at intersections, and misaligned objectives as key failure modes, show a synthetic positive control where future information reduces rollout cost by 61.5%, but find that on frozen test dates causal forecasts and an event oracle increased queue vehicle-seconds versus a matched no-future rollout.