Abstract:

Intelligent driving technology has the potential to enhance the safety and efficiency of road transportation systems, drive innovation and technological breakthroughs within the automotive industry and its upstream and downstream supply chain ecosystems, and serve as a critical area of competition among leading industrial nations. After decades of development and with continuous advancements driven by the Internet and artificial intelligence technologies, intelligent driving technology is approaching the threshold of large-scale commercial application. This paper provides a systematic review of the development trajectory of intelligent driving technology, summarizes the current state of technological progress in hardware support systems, software functionality systems, and “end-to-end” autonomous driving systems, analyzes key technical issues and challenges faced by various functional modules, and offers insights into future development trends. The findings aim to provide scientific guidance and strategic recommendations for the further development and application of advanced autonomous driving technologies in China.

Key words: intelligent driving, “end-to-end”, perception and prediction, decision-making and planning, simulation and testing, closed loop of data

摘要：

智能驾驶技术作为提升交通安全与效率、推动汽车产业革新的核心领域，已进入高级别自动驾驶量产应用的关键阶段。文章系统梳理了智能驾驶技术的发展历程，从硬件支持系统（车载芯片、传感器、控制器、执行器等）、软件功能系统（操作系统、地图与定位、环境感知、预测决策、运动控制、仿真测试等），以及“端到端”自动驾驶系统（数据采集和标注、训练算法、模型架构、压缩部署等）3方面总结技术现状。揭示其面临的共性挑战：硬件能效与安全瓶颈、传感器融合精度不足、开放道路长尾场景泛化能力弱、大规模模型算力需求激增、仿真测试覆盖不足及数据安全风险等。未来技术将向硬件融合一体化、软件高稳定性与安全性、“端到端”车路云协同赋能方向演进。针对中国发展需求，提出加强硬件自主可控、构建国产软件生态、建立统一测试评价体系及推动“端到端”技术落地的对策建议，以期为高级别自动驾驶技术突破与产业化提供理论支撑。

关键词: 智能驾驶, “端到端”, 感知预测, 决策规划, 仿真测试, 数据闭环