NVIDIA DGX Spark
Awarded to the Track 1 winner. Personal AI supercomputer for desktop development and inference.
Autonomous driving stacks behave well on the head of the distribution, but the long tail — rare, ambiguous, or interactive scenarios — is where most safety-critical failures occur. This challenge invites the research community to build models that can reason about these long-tail scenarios in natural language, building on NVIDIA's public PAI-AV Dataset.
Models will be evaluated on a curated out-of-distribution test set mined from a large physical-AI autonomous-driving corpus. Each scenario is anchored at a precise keyframe and annotated with a chain-of-causation describing the relevant agents, interactions, and the appropriate ego behavior.
The 2026 edition has two tracks: a chain-of-causation reasoning-generation track, and an open auto-labeling leaderboard for the research community.
Input: a multi-camera driving clip and an event window.
Output: a free-form natural-language explanation that identifies
the relevant agents, the interactions that make the scenario challenging,
and the recommended ego behavior at the keyframe.
Submission format, evaluation protocol, and scoring details will be released on June 15, 2026.
Input: the validation clips of the out-of-distribution reasoning set.
Output: automatically generated chain-of-causation reasoning labels
for each clip.
Submission format and details released on June 15, 2026.
Dates are tentative and subject to update.
The winner of Track 1 will be awarded an NVIDIA DGX Spark. Track 2 runs as a leaderboard-only benchmark for the community.
Awarded to the Track 1 winner. Personal AI supercomputer for desktop development and inference.
This competition is hosted by NVIDIA's Autonomous Vehicle Research Group.
HostInterdisciplinary NVIDIA Research team advancing vehicle autonomy across perception, prediction, planning, control, simulation, foundation models, and AI safety.
Bookmark this page — full challenge details, evaluation methodology, and submission instructions will be published when the evaluation server opens.