Summary of Promptable Closed-loop Traffic Simulation, by Shuhan Tan et al.
Promptable Closed-loop Traffic Simulation
by Shuhan Tan, Boris Ivanovic, Yuxiao Chen, Boyi Li, Xinshuo Weng, Yulong Cao, Philipp Krähenbühl, Marco Pavone
First submitted to arxiv on: 9 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A multimodal promptable closed-loop traffic simulation framework, ProSim, is proposed for autonomous driving development. It enables users to provide complex prompts, numerical, categorical, or textual, to instruct agents’ behaviors and intentions. The system simulates realistic, reactive, and controllable traffic patterns in a closed-loop manner, modeling each agent’s interactions with other traffic participants. Experiments show that ProSim achieves high prompt controllability while reaching competitive performance on the Waymo Sim Agents Challenge without prompts. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ProSim is a new tool for creating real-life traffic simulations. It lets users tell agents what to do and how to behave in different situations. The system makes traffic scenarios look realistic, and it can even change its behavior based on what’s happening around it. Researchers will find ProSim useful for studying how to make autonomous cars work better. |
Keywords
» Artificial intelligence » Prompt
