Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives

S **e, L Kong, Y Dong, C Sima, W Zhang… - arxiv preprint arxiv …, 2025‏ - arxiv.org
Recent advancements in Vision-Language Models (VLMs) have sparked interest in their use
for autonomous driving, particularly in generating interpretable driving decisions through …

VDT-Auto: End-to-end Autonomous Driving with VLM-Guided Diffusion Transformers

Z Guo, K Gubernatorov, S Asfaw, Z Yagudin… - arxiv preprint arxiv …, 2025‏ - arxiv.org
In autonomous driving, dynamic environment and corner cases pose significant challenges
to the robustness of ego vehicle's decision-making. To address these challenges …

VLM-E2E: Enhancing End-to-End Autonomous Driving with Multimodal Driver Attention Fusion

P Liu, H Liu, H Liu, X Liu, J Ni, J Ma - arxiv preprint arxiv:2502.18042, 2025‏ - arxiv.org
Human drivers adeptly navigate complex scenarios by utilizing rich attentional semantics,
but the current autonomous systems struggle to replicate this ability, as they often lose …