Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation
Yang, Xiuyu, Tan, Shuhan, Krähenbühl, Philipp
–arXiv.org Artificial Intelligence
Prior models and benchmarks focus on closed-loop motion simulation for initial agents in a scene. This is problematic for long-term simulation. Agents enter and exit the scene as the ego vehicle enters new regions. W e propose InfGen, a unified next-token prediction model that performs interleaved closed-loop motion simulation and scene generation. InfGen automatically switches between closed-loop motion simulation and scene generation mode. It enables stable long-term rollout simulation. InfGen performs at the state-of-the-art in short-term (9s) traffic simulation, and significantly outperforms all other methods in long-term (30s) simulation.
arXiv.org Artificial Intelligence
Aug-6-2025
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