" 更低成本的真实数据需求，更快迭代智驾系统。 " 作者丨田哲 编辑丨林觉民 4月23日，第二十一届上海国际车展上，商汤绝影发布了包括生成式智驾R-UniAD、4D世界模型"绝影开 悟2.0"、AI内核"绝影千机"在内的多个核心技术。 统观绝影发布的技术，一句话概括为：不是做"功能模型"，而是做"系统AI"。 过去几年，端到端技术被认为是智能驾驶实现路径中的"终极形态"，但大多数方案都卡在数据、性能、安 全三道门槛前。R-UniAD的思路，是在这三道门槛外，再造一层AI基础设施。 据介绍，R-UniAD结合世界模型和强化学习，以VLAR（视觉、语言、行动、强化学习）技术架构为核 心，支持仿真环境中进行闭环训练，让模型能在虚拟世界里"试错—强化—泛化"，最终形成系统策略能 力。 以车展现场展示的"施工占道场景"为例，R-UniAD先通过"绝影开悟"世界模型构建4D动态环境，再让模 型反复在这个世界里强化训练不同策略。最终结果是，模型不仅能精准避让，还能泛化到其它类似场景 中。 这种能力的意义在于，它不仅降低了数据成本，更提高了模型上限——在少数据场景里跑出更强泛化能 力，是当前行业少见的尝试。 如果说R-Uni ...

Core Viewpoint - The collaboration between SenseTime and Dongfeng Motor in the field of intelligent driving represents a deep integration of technology and industry, providing a practical model for the sector [1] Technological Breakthroughs - SenseTime showcased the R-UniAD solution based on the VLAR architecture, achieving near real-time interactive simulation and reducing the need for real data by two orders of magnitude [3] - The system demonstrated a perception accuracy of 98% compared to real data and improved simulation efficiency by five times over industry benchmarks [3] - The joint team has made significant progress in developing an end-to-end autonomous driving system, which features a "dual insurance" architecture combining a learning-based decision system with a rule-driven safety redundancy [3] Industry Collaboration - SenseTime has partnered with four car manufacturers, covering seven vehicle models, and plans to mass-produce an end-to-end solution based on the NVIDIA Thor platform by Q4 2025 [3] - The company has maintained a leading market share in intelligent cockpit software for five consecutive years, with cumulative deliveries exceeding 3.6 million units [3] Ecological Evolution - SenseTime introduced the first in-vehicle AI operating system, "Jueying Qianji," with a response latency of less than 300ms, supporting over 100 intelligent agents [6] - The upgraded "New Member" system showcases multimodal recognition and deep thinking capabilities, providing personalized services during real-time demonstrations [6] - The "Travel Medical" system integrates medical-grade health monitoring and connects with third-party medical services [8] Industry Observations - The recent regulatory adjustments are viewed as a turning point towards maturity rather than a pause in the intelligent transformation process [8] - The penetration rate of L2-level assisted driving reached 62% in 2024, with a 37% year-on-year increase in user complaints regarding functional safety [8] - The collaboration model between Dongfeng and SenseTime reflects a dual-track strategy of "independent control + open collaboration" in the intelligent transformation of traditional car manufacturers [8] Common Industry Challenges - The introduction of AI-native technologies like world models and reinforcement learning is breaking through the limitations of rule-driven systems [11] - There is an urgent need to establish compliant data collection systems and unified safety assessment standards within the industry [11] - The deep binding of AI companies and vehicle manufacturers may be a key pathway to address these common challenges [11]