TrafficGamer: Reliable and Flexible Traffic Simulation for Safety-Critical Scenarios with Game-Theoretic Oracles

arXiv:2408.15538 · cs.AI, cs.MA · Submitted 2024-08-28 · Read on arXiv

cs.AI, cs.MA

Submitted: 2024-08-28

Updated: 2026-09-15

Comments: 2026 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Project page: https://anonymous.4open.science/api/repo/trafficgamer-demo-1EE0/file/index.html

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Fidelity — 20× in this paper · explained in 2 episodes
• World Model — 20× in this paper · explained in 7 episodes
• Reinforcement Learning — 13× in this paper · explained in 4 episodes
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Autonomous Vehicle — 5× in this paper
• Correlated Equilibrium — 5× in this paper
• Coarse Correlated Equilibrium — 4× in this paper
• Robustness — 4× in this paper · explained in 5 episodes
• Steering — 4× in this paper · explained in 2 episodes
• Actor — 3× in this paper · explained in 3 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Nash Equilibrium — 3× in this paper · explained in 2 episodes
• Reward Function — 3× in this paper · explained in 2 episodes
• Cooperation — 2× in this paper · explained in 2 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Predictive Modeling — 2× in this paper · explained in 2 episodes
• Q-learning — 2× in this paper · explained in 3 episodes
• Wasserstein Distance — 2× in this paper · explained in 4 episodes
• Waymo Open Motion Dataset — 2× in this paper
• Ablation — 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
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adversarial scenarios — 1× in this paper · explained in 1 episode
• Agent Interactions — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Conditional Value-at-Risk — 1× in this paper
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Magnetic Mirror Descent — 1× in this paper
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Partially Observable Constrained Markov Decision Process — 1× in this paper
• Regret — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Time to Collision — 1× in this paper
• Transformer — 1× in this paper · explained in 2 episodes
• Two-Phase Framework — 1× in this paper · explained in 2 episodes

Sources

• Versatile Behavior Diffusion for Generalized Traffic Agent Simulation

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