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Pages tagged benchmark
Dosovitskiy, Ros, Codevilla, Lopez, Koltun (Intel Labs / Toyota Research Institute / CVC Barcelona), CoRL, 2017. 📄 **[Read on arXiv](https://arxiv.org/abs/1711.03938)** CARLA (Car Learning to Act) is an open-source simu…
📄 **[Read on arXiv](https://arxiv.org/abs/2312.14150)** DriveLM formalizes driving reasoning as Graph Visual Question Answering (GVQA), where QA pairs are connected via logical dependencies forming a reasoning graph tha…
[Read on arXiv](https://arxiv.org/abs/2312.03031) This paper (CVPR 2024, NVIDIA / Nanjing University) delivers a "wake-up call" to the autonomous driving research community by demonstrating that simple baselines using o…
:page_facing_up: **[Read on arXiv](https://arxiv.org/abs/2406.15349)** Autonomous vehicle evaluation has long been split between two unsatisfying extremes: open-loop metrics that replay logged trajectories and compare p…
📄 **[Read on arXiv](https://arxiv.org/abs/1903.11027)** nuScenes is a large-scale multimodal dataset for autonomous driving that provides synchronized data from 6 cameras (360-degree coverage), 1 LiDAR, 5 radars, GPS, a…
:page_facing_up: **[Read on arXiv](https://arxiv.org/abs/2506.04218)** Pseudo-Simulation by Cao, Hallgarten et al. (Tubingen / Shanghai AI Lab / NVIDIA / Stanford, CoRL 2025) introduces a novel evaluation paradigm for a…
📄 **[Read on arXiv](https://arxiv.org/abs/2312.03661)** Reason2Drive provides the largest reasoning chain dataset for driving (>600K video-text pairs from nuScenes, Waymo, and ONCE) and introduces an aggregated evaluati…
📄 **[Read on arXiv](https://arxiv.org/abs/1909.10838)** For autonomous vehicles to be truly useful as personal transportation, passengers should be able to issue natural-language commands like "park behind that blue car…
📄 **[Read on arXiv](https://arxiv.org/abs/1807.11546)** End-to-end driving models produce control signals without any rationale, making them opaque and untrustworthy for safety-critical deployment. This paper by Kim et…