浅聊小鹏、理想、特斯拉最新智驾架构

Ofweek光电信息网2025-05-06

小鹏汽车小鹏汽车的智能驾驶系统（XPILOT）硬件架构非常先进，最新的G9车型搭载了双Nvidia Orin芯片，总算力达508 TOPS，并配备了12个摄像头、5个毫米波雷达、12个超声波雷达以及2颗激光雷达。其中两颗激光雷达作为视觉感知的补盲传感器使用，而非唯一依赖；高分辨率的摄像头使其能够远距离识别场景。在软件方面，小鹏采用模块化的感知体系并结合端到端的规划网络。XPILOT多年来通过不断...

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TOPS）和禾赛128线激光雷达。软件架构方面，理想采用了“快慢双系统”策略，使用端到端网络负责低延迟的实时控制（快系统），同时引入视觉语言大模型增强对复杂场景的理解（慢系统）。理想过去一年通过在端到端模型之外叠加VLM，利用大模型来解析语义信息（例如交通标志含义、行人行为推理等），以辅助端到端模型进行决策。该方案在现实计算资源下仍占用了整颗Orin-X算力，双模型的协同效率有待提升。据报道，理想计划在2025年下半年推出下一代VLA（视觉-语言-动作）端到端大模型，将视觉和语言能力深度耦合，进一步提升模型的多模态推理能力，并有望显著降低人工接管率。理想的应用场景主要以家庭高速游览为主，也在测试城市道路自动辅助驾驶，其特点是注重安全性（大量冗余传感和算力备份）以及逐步向大模型方向发展。特斯拉特斯拉作为自动驾驶领域的先锋，目前已几乎完全采用纯视觉架构。其最新硬件（HW4）集成了8个环视摄像头，加上一些毫米波雷达单元（2021年后曾去除，后又部分恢复）以及两个自研FSD芯片，总算力级别也在数百TOPS量级。与前两者不同，特斯拉并不使用激光雷达和高精地图，其规划系统完全依赖基于深度学习的视觉和雷达感知结果。2023年特斯拉公开的资料显示，其最新FSD 版本采用了端到端的BEV占据网络进行路径规划。该网络从多摄像头拼接出的BEV语义图中直接预测可行驶空间，从而生成车辆轨迹。这种规划方法弱化了对事先道路拓扑的依赖，通过数据驱动的方式学习环境语义，有助于多传感器信息的融合。特斯拉的应用场景从美国高速公路一路扩展到全球城市街道，其FSD Beta在有限条件下可完成复杂路口及高速匝道等任务。总体而言，特斯拉的特点是End-to-End First，系统设计简化为几层网络联合优化，以大量实车数据驱动模型迭代，不断通过OTA推送来改进驾驶策略，其决策机制完全由神经网络学习实现，黑箱化程度较高。-- END 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