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车路协同感知技术研究进展及展望
Vehicle‒Infrastructure Cooperative Sensing: Progress and Prospect
近年来，我国自动驾驶研究逐步从聚焦于单车智能技术向车路协同技术转变，为智能交通产业发展带来了重大机遇；我国在车路协同感知领域的研究虽处于起步阶段，但注重技术推动，未来发展前景广阔。本文致力于深入探讨车路协同感知技术的发展动态，梳理了车路协同感知基础支撑技术的特性和发展现状，厘清了车路协同感知技术的研究进展，探讨了其技术发展趋势，并针对推动车路协同感知技术发展提出了一系列建议。研究表明，车路协同感知技术正朝着多源数据融合方向发展，主要集中在纯视觉协同感知技术优化、激光雷达点云处理技术升级、多传感器时空信息匹配与数据融合技术发展以及车路协同感知技术标准体系构建等方面。为进一步促进我国车路协同自动驾驶产业的迅速成长，研究建议，加大对多模态车路协同感知技术的研发投入、深化行业间的合作、制定统一的感知数据处理技术标准并加速技术应用普及，以期推动我国在全球自动驾驶竞争中赢得主动，推动自动驾驶行业稳定持续发展。
Recently, the autonomous driving industry in China has been gradually shifting its focus from individual-vehicle intelligence to vehicle‒infrastructure cooperation. This shift has brought significant opportunities for the intelligent transportation industry. Although research on vehicle‒infrastructure cooperative sensing is still in its early stage in China, it shows a strong dedication to technological innovation, indicating significant potentials for future growth. This study examines the development status of vehicle‒infrastructure cooperative sensing and thoroughly explores the characteristics and status of core technologies that support vehicle‒infrastructure cooperative sensing. It discusses ongoing advancements in this field, investigates future technology trends, and proposes a range of recommendations for further development. Research indicates that vehicle‒infrastructure cooperative sensing is evolving toward the integration of multi-source data. Presently, its development directions mainly focus on the optimization of pure visual cooperative sensing, upgrades in LiDAR point cloud processing, advancements in multi-sensor spatiotemporal information matching and data fusion, as well as the establishment of a standards system for vehicle‒infrastructure cooperative sensing technologies. To further boost the rapid growth of vehicle‒infrastructure cooperation in China, increasing investment in the research and development of relevant technologies is advised. Enhancing partnerships among different industry sectors, establishing unified standards for processing perception data, and expediting the broad application of these technologies are also key recommendations. These strategies aim to position China advantageously in the global market of autonomous driving, contributing to the sustainable development of the industry.
自动驾驶 / 车路协同感知 / 多源数据 / 激光雷达 / 视频摄像机 / 标准体系
autonomous driving / vehicle‒infrastructure cooperative sensing / multi-source data / LiDAR / video camera / standards system
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