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SimSkill is a lifelong learning AI agent that autonomously masters traffic simulation by identifying capability gaps, generating tasks, and using memory systems to improve performance, showing up to 25% improvement in task completion on benchmarks.
This paper proposes a simulation-based methodology to generate augmented traffic datasets by replacing physical sensors with virtual ones, extending sensor coverage in urban networks while preserving traffic patterns.
Flow-ERD is a multi-agent traffic simulator that combines agent-type aware flow matching with entropy-regularized distillation to achieve both realistic and diverse motion patterns, ranking first on the WOSAC test benchmark.
Introduces RosettaSim, a framework that uses structured autoregressive modeling for long-term traffic simulation, achieving state-of-the-art performance on the Waymo Open Sim Agent Challenge. Also proposes Retrieval-based Traffic Evaluation (RTE) for better long-horizon fidelity assessment.
Archi-Flow is a tool that visualizes cloud architecture with live traffic simulations.