CoLT-Drive - Road Hazard: leaderboard

Metric: Pair accuracy (%; the 348 v_full samples, naturalistic surrounding traffic kept, whose inserted object is one of the road-surface hazards (potholes, open manholes, oil spills, glass and cables), where the model outputs an acceptable longitudinal-lateral meta-action pair for a front-view driving image with a counterfactually inserted rare object, ego-motion history and navigation command; human-adjudicated acceptable-pair sets; same structured prompt and greedy decoding for every model; decisions extracted by rule and normalized by a text-only DeepSeek-V4-Pro mapper, then scored deterministically; invalid outputs count as wrong). Source: arxiv.org. Saturation forecast: Around December 2026. 9 models tracked.

Top models

#ModelScore
1GPT-5.579.3
2Qwen 3 VL 8B51.1

Interactive version: theaggregate.ai/benchmark?slug=colt-drive-road-hazard · How It Works · Data refreshed daily, snapshot 2026-09-26.