中国百度（9888.HK）周二推出 Apollo World，这是一个旨在模拟真实环境以训练 Robotaxi 并预测其演变的 AI 系统，正值车企竞相降低自动驾驶汽车开发成本之际。
China's Baidu (9888.HK) launched Apollo World on Tuesday, an AI system designed to simulate real-world environments for training robotaxis and predict how they evolve, as automakers race to cut the cost of developing autonomous vehicles.
百度表示，Apollo World 每天可生成“高达 10 万公里”（约 6.2 万英里）的模拟驾驶里程，相当于配备安全员的自动驾驶汽车约三年的真实路测里程。该系统能够生成实时多模态数据流，例如摄像头和激光雷达观测数据，使自动驾驶系统能够直接感知并导航模拟环境。
Apollo World can generate "up to 100,000 km" (62,000 miles) of simulated driving daily, equivalent to about three years of real-world testing by a safety-driver-equipped autonomous vehicle, Baidu said. The system is capable of producing real-time multimodal data streams, such as camera and lidar observations, enabling self-driving systems to directly sense and navigate simulated environments.
百度称，Apollo World 已用于训练面向全球运营的 Apollo Go Robotaxi 车队。百度旗下的 Apollo Go 是中国最大的 Robotaxi 服务运营商，与文远知行（WRD.O）、小马智行（PONY.O）和纵目科技（6880.HK）等竞争对手展开竞争。
Baidu said Apollo World is already being used for training Apollo Go’s robotaxi fleet to be operated globally. Baidu-owned Apollo Go is China's largest robotaxi service operator and competes with rivals such as WeRide (WRD.O), Pony.ai (PONY.O) and Momenta Global (6880.HK).
大众汽车的中国合作伙伴小鹏汽车（9868.HK）也计划于 2027 年启动 Robotaxi 运营。
Volkswagen's Chinese partner XPeng (9868.HK) also plans to launch robotaxi operations in 2027.
摩根士丹利估计，中国的 Robotaxi 车队规模到 2035 年可能增长至 100 万辆。
Morgan Stanley has estimated China's robotaxi fleet could grow to 1 million vehicles by 2035.
中国 Robotaxi 企业主要采取轻资产扩张策略，向海外的车企、网约车平台和当地车队运营商提供自动驾驶技术并建立合作伙伴关系，而非承担拥有和运营车队的全部成本。但开发技术本身仍然昂贵。
Chinese robotaxi firms have largely pursued asset-light expansion strategies, supplying autonomous-driving technology and partnering with automakers, ride-hailing platforms and local fleet operators overseas rather than bearing the full cost of owning and operating fleets. But developing the technology itself remains expensive.
管理咨询公司罗兰贝格自动驾驶出行与城市交通专家 Frank McCleary 表示：“它们仍然面临训练模型……和车辆的资本性支出，这是每家自动驾驶汽车公司都将面临的挑战。”
"They still have the capex of training models ... and vehicles, a challenge that every autonomous vehicle company is going to face," said Frank McCleary, an expert in autonomous mobility and urban transportation at management consulting firm Arthur D. Little.
他补充道：“你能多快推出服务，取决于你的技术适应、理解并学习（如何在）该环境中驾驶的能力，”并指出 AI 已帮助加速自动驾驶的进步。
"The speed at which you can launch comes down to your technology's ability to adapt and understand and learn (how to drive in) that environment," he said, adding AI has helped accelerate advances in autonomous driving.
特斯拉（TSLA.O）正寻求扩大其 Cybercab 无人驾驶出租车车队，该公司采用一种“端到端神经网络”，通过人类驾驶视频进行训练，以开发其自动驾驶技术。
Tesla (TSLA.O), which is seeking to expand its Cybercab robotaxi fleet, uses an "end-to-end neural network" trained on video of human driving to develop its self-driving technology.