MDRC: A Deployable State-Recovery Defense for Traffic Signal Control under Sensor Corruption

arXiv:2609.27528 · cs.CR · Submitted 2026-09-23 · Read on arXiv

cs.CR

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Meta-learning — 34× in this paper · explained in 2 episodes
• Traffic Signal Control — 18× in this paper
• Reinforcement Learning — 16× in this paper · explained in 4 episodes
• Adaptation — 15× in this paper · explained in 1 episode
• Robustness — 15× in this paper · explained in 5 episodes
• Average Travel Time — 10× in this paper
• Generalization — 7× in this paper · explained in 13 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Diffusion Model — 6× in this paper · explained in 8 episodes
• Trace — 5× in this paper · explained in 2 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Adam — 4× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Denoising Diffusion Implicit Models — 3× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Core — 2× in this paper · explained in 2 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Diffusion Process — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Score Function — 2× in this paper · explained in 4 episodes
• Wasserstein Distance — 2× in this paper · explained in 4 episodes
• Zero-Shot Transfer — 2× in this paper · explained in 4 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Continual Learning — 1× in this paper · explained in 2 episodes
• Cooperation — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Maximize Action Difference — 1× in this paper
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Network and Distributed System Security — 1× in this paper
• Online Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Stochastic Gradient Descent (SGD) — 1× in this paper · explained in 5 episodes

Sources

• Efficient Pressure: Improving efficiency for signalized intersections
• Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks
• FuzzyLight: A Robust Two-Stage Fuzzy Approach for Traffic Signal Control Works in Real Cities
• ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control
• Denoising Diffusion Implicit Models
• On First-Order Meta-Learning Algorithms
• Meta-Learning with Latent Embedding Optimization
• Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
• Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
• Classifier-Free Diffusion Guidance
• Score-Based Generative Modeling through Stochastic Differential Equations

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