SignalClaw synthesizes interpretable, composable traffic signal control skills through LLM-guided evolution that matches top baselines on routine SUMO scenarios and outperforms them on emergency and transit events while remaining editable by engineers.
Max pressure control of a network of signalized inter- sections
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
FairSCOSCA extends deployed arterial signal controllers with waiting-time optimization and early phase termination to improve egalitarian, Rawlsian, utilitarian, and Harsanyian fairness metrics in simulation while preserving traffic efficiency.
citing papers explorer
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SignalClaw: LLM-Guided Evolutionary Synthesis of Interpretable Traffic Signal Control Skills
SignalClaw synthesizes interpretable, composable traffic signal control skills through LLM-guided evolution that matches top baselines on routine SUMO scenarios and outperforms them on emergency and transit events while remaining editable by engineers.
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FairSCOSCA: Fairness At Arterial Signals -- Just Around The Corner
FairSCOSCA extends deployed arterial signal controllers with waiting-time optimization and early phase termination to improve egalitarian, Rawlsian, utilitarian, and Harsanyian fairness metrics in simulation while preserving traffic efficiency.