百度发布 Apollo World 世界模型，用于自动驾驶仿真训练
百度发布的世界模型 Apollo World，能把驾驶场景变成可控仿真来训练 Apollo Go，连传感器数据都实时生成。
百度在深圳 AI Day 上发布面向物理 AI 的世界模型 Apollo World。该模型能把道路上的复杂交互和稀有驾驶场景转化为可重复、可控的仿真环境，供自动驾驶系统训练与测试使用。Apollo World 具备三类能力：自主决策的 AI 交通智能体会随车辆减速、变道、让行而做出反应；实时生成相机、LiDAR 等传感器数据，让虚拟世界随车辆动作而变化；支持从接单到落客的完整虚拟城市行程。该技术栈也适用于机器人等其他物理 AI 场景，目前已接入 Apollo Go 的测试验证流程。
Apollo World, our world model for physical AI, was unveiled yesterday at Baidu AI Day in Shenzhen!
It turns complex interactions on the road and rare driving scenarios into repeatable, controllable simulations for training and testing autonomous driving systems. - AI traffic agents that make their own decisions and react as autonomous vehicles slow down, change lanes, or yield - Simulated camera, LiDAR, and other sensor data generated in real time, helping autonomous vehicles sense and respond to a virtual world that changes with their actions - Complete rides between any two locations in a virtual city, from accepting a ride request to dropping off passengers - A technology stack suited to robotics and other physical AI applications
Apollo World is already part of Apollo Go's testing and validation. What we learn from those virtual trips helps us improve how the vehicles drive on real roads.
