研究人员推出了 KITScenes Multimodal，一个用于自动驾驶的新欧洲数据集，该数据集具有高保真传感器和全面的高清地图。该数据集旨在解决现有数据集在传感器保真度、地图完整性和地理多样性方面的局限性。此外，还开发了一个名为 Action Diffusion Transformer (ADT) 的新模型，用于端到端自动驾驶，该模型利用多模态动作预测来提高性能和稳定性。 AI
影响 新的多模态数据集和动作建模方法有望加速鲁棒端到端自动驾驶系统的研究。
排序理由 该集群包含两篇详细介绍自动驾驶新数据集和模型的学术论文。
AI 生成摘要 · Google Gemini · 来自 4 个来源。 我们如何撰写摘要 →
arXiv:2606.02956v1 Announce Type: cross Abstract: Existing autonomous driving datasets have enabled major progress, but fall short in sensor fidelity, map completeness, or geographic diversity. We present KITScenes Multimodal, a European dataset built around high-fidelity sensors…
KITScenes Multimodal dataset provides high-fidelity European driving data with comprehensive 3D maps and diverse urban environments for embodied AI research.
arXiv:2606.02105v1 Announce Type: new Abstract: End-to-End Autonomous Driving (E2E-AD) systems have largely converged on predicting intermediate trajectory waypoints, delegating final control to hand-crafted controllers with GPS access. Direct control-signal prediction (outputtin…
End-to-End Autonomous Driving (E2E-AD) systems have largely converged on predicting intermediate trajectory waypoints, delegating final control to hand-crafted controllers with GPS access. Direct control-signal prediction (outputting throttle, steer and brake in an end-to-end fas…