Entity embeddings of lanes and phases plus hierarchical attention and action masking yield an explainable PPO traffic-signal controller that matches or beats baselines on delay while producing attention maps aligned with queue and phase logic.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Explainable Reinforcement Learning for Adaptive Traffic Signal Control
Entity embeddings of lanes and phases plus hierarchical attention and action masking yield an explainable PPO traffic-signal controller that matches or beats baselines on delay while producing attention maps aligned with queue and phase logic.