2023/06/20 by Yu Wang, Wang, Yu, Tiebiao Zhao +3 · 6 citations
Computer Science · Decision Sciences · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Modeling and Simulation Systems #Real-time simulation and control systems #Simulation Techniques and Applications
paper · pdf · doi:10.48550/arxiv.2306.11868
openalex publication_date 2023/06/20 · openalex created_date 2023/06/24 · openalex updated_date 2026/07/28
This technical report presents our 1st place solution for the Waymo Open Sim Agents Challenge (WOSAC) 2023. Our proposed MultiVerse Transformer for Agent simulation (MVTA) effectively leverages transformer-based motion prediction approaches, and is tailored for closed-loop simulation of agents. In order to produce simulations with a high degree of realism, we design novel training and sampling methods, and implement a receding horizon prediction mechanism. In addition, we introduce a variable-length history aggregation method to mitigate the compounding error that can arise during closed-loop autoregressive execution. On the WOSAC, our MVTA and its enhanced version MVTE reach a realism meta-metric of 0.5091 and 0.5168, respectively, outperforming all the other methods on the leaderboard.