CES 2026 | NVIDIA 推出 Alpamayo 系列开源 AI 模型与工具，加速安全可靠的推理型辅助驾驶汽车开发

车东西01-13

NVIDIA 率先发布为应对辅助驾驶长尾场景挑战而设计的开源视觉-语言-动作推理模型（Reasoning VLA）；NVIDIA Alpamayo 系列还包含赋能辅助驾驶汽车开发的仿真工具和数据集。Alpamayo 1、AlpaSim 和物理 AI 开放数据集可为开发具备感知、推理与类人决策能力的车辆提供支持，使开发者能够进行模型调优、蒸馏和测试，从而提升安全性、鲁棒性与可扩展性。捷豹路虎、...

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vehicles","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"NVIW.SI":0.6,"NVDS.UK":0.6,"NVDD":0.6,"NVDL":0.6,"NVDU":0.6,"NVDA":1.97,"2NVD.UK":0.6,"3NVD.UK":0.6,"NVD2.UK":0.6,"NVDY":0.6,"NVD3.UK":0.6,"NVD":0.6,"NVDS":0.6,"NVDX":0.6,"SNVD.UK":0.6},"content_text":"NVIDIA 率先发布为应对辅助驾驶长尾场景挑战而设计的开源视觉-语言-动作推理模型（Reasoning VLA）；NVIDIA Alpamayo 系列还包含赋能辅助驾驶汽车开发的仿真工具和数据集。Alpamayo 1、AlpaSim 和物理 AI 开放数据集可为开发具备感知、推理与类人决策能力的车辆提供支持，使开发者能够进行模型调优、蒸馏和测试，从而提升安全性、鲁棒性与可扩展性。捷豹路虎、Lucid 和 Uber 等移动出行领域领先企业，以及包括伯克利 DeepDrive 在内的自动驾驶研究社区，将依托 Alpamayo 加速推进安全的推理型 L4 级部署进程。NVIDIA 发布 NVIDIA Alpamayo 系列开源 AI 模型、仿真工具及数据集，旨在推动安全可靠的推理型辅助驾驶汽车开发。智能汽车必须在复杂多变的驾驶条件下安全运行。被称为“长尾”的罕见、复杂场景始终是辅助驾驶系统需要攻克的最大难题之一。传统辅助驾驶架构将感知与规划分离开来，这在面临突发或异常状况时，往往会限制其系统扩展性。尽管端到端学习的最新进展已取得显著突破，但要解决这些长尾极端事件，仍需具备安全推理因果关系能力的模型，特别是在遇到的场景超出模型训练经验的情况下。Alpamayo 系列引入基于思维链的 VLA 推理模型，为辅助驾驶决策注入类人的思维能力。这些系统能够逐步推演罕见或全新场景，提升驾驶能力和可解释性，这对构建智能汽车的安全信任体系至关重要，其核心技术由 NVIDIA Halos 安全系统提供支撑。NVIDIA 创始人兼首席执行官黄仁勋表示：“物理 AI 的 ChatGPT 时刻已然到来，机器开始具备理解真实世界、推理并付诸行动的能力。无人驾驶出租车将是最早受益的应用之一。Alpamayo 为智能汽车注入推理能力，使其得以应对罕见场景、在复杂环境中安全行驶，并解释其驾驶决策，这为安全、可规模化的自动驾驶奠定了基础。”Lucid、捷豹路虎、Uber 和伯克利 DeepDrive 等移动出行领域的领先企业和业界专家展现了对 Alpamayo 的极高关注，希望开发基于推理的自动驾驶堆栈，以实现 L4 级自动驾驶。","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"productRelease","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":1,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; 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