The Waymo Open Sim Agents Challenge

N. Montali, John Lambert, Paul Mougin, Alex Kuefler, Nick Rhinehart +7 more
2/12/2026

No official code found. Best implementation: wangwenxi-handsome/Joint-Multipathpp (31 stars, last commit 2023-09-06).

Abstract

Simulation with realistic, interactive agents represents a key task for autonomous vehicle software development. In this work, we introduce the Waymo Open Sim Agents Challenge (WOSAC). WOSAC is the first public challenge to tackle this task and propose corresponding metrics. The goal of the challenge is to stimulate the design of realistic simulators that can be used to evaluate and train a behavior model for autonomous driving. We outline our evaluation methodology, present results for a number of different baseline simulation agent methods, and analyze several submissions to the 2023 competition which ran from March 16, 2023 to May 23, 2023. The WOSAC evaluation server remains open for submissions and we discuss open problems for the task.

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Code Implementations(1)

wangwenxi-handsome/Joint-MultipathppCommunity100%

Joint Multipath++(2nd) for Sim Agent in waymo competition 2023 of CVPR workshop

316PythonApr 18, 20233 years ago

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Cite this paper

@article{montali2026waymo,
  title  = {The Waymo Open Sim Agents Challenge},
  author = {N. Montali and John Lambert and Paul Mougin and Alex Kuefler and Nick Rhinehart and Michelle Li and Cole Gulino and Tristan Emrich and Zoey Yang and Shimon Whiteson and B. White and Drago Anguelov},
  year   = {2026},
  eprint = {2305.12032},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/pdf/2305.12032},
  journal = {NEURIPS 2023 2023}
}

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