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车路协同感知技术研究进展及展望OA北大核心CSTPCD

Vehicle‒Infrastructure Cooperative Sensing:Progress and Prospect

中文摘要英文摘要

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.

伊笑莹;芮一康;冉斌;罗开杰;孙虎成

东南大学交通学院,南京 211189中国公路学会,北京 100011

交通运输

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 drivingvehicle‒infrastructure cooperative sensingmulti-source dataLiDARvideo camerastandards system

《中国工程科学》 2024 (001)

面向车路协同的动态高精地图时空一体化建模

178-189 / 12

中国工程院咨询项目"车路协同自动驾驶系统研究"(2022-XBZD-19);国家自然科学基金项目(41971342);江苏省研究生科研与实践创新计划项目(SJCX23_0073);山东省重点研发计划项目(2020CXGC010118) Chinese Academy of Engineering project"Research on Vehicle‒Infrastructure Cooperative Autonomous Driving Systems"(2022-XBZD-19);National Natural Science Fund Project(41971342);Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX23_0073);Key R&D Program Project in Shandong Province(2020CXGC010118)

10.15302/J-SSCAE-2024.01.016

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