中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Software-Defined Active LiDARs for Autonomous Driving: A Parallel Intelligence-Based Adaptive Model

文献类型:期刊论文

作者Liu, Yuhang1,7; Sun, Boyi5; Tian, Yonglin4,6; Wang, Xingxia1,7; Zhu, Yin3; Huai, Rouxing2; Shen, Yu1,7
刊名IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
出版日期2023-08-01
卷号8期号:8页码:4047-4056
ISSN号2379-8858
关键词Software-defined active LiDARs parallel intelligence adaptive sensing resources allocation
DOI10.1109/TIV.2023.3289540
通讯作者Shen, Yu(shenyu2015@ia.ac.cn)
英文摘要LiDAR is an indispensable sensor for autonomous driving that can provide precise 3D information about the environment. Among various types of LiDARs, mechanical LiDARs are the most commonly used on vehicles that uniformly perceive the scene utilizing rotating motors. However, accurate perception of foreground objects is considered as the most important task in automotive LiDARs, therefore the current operating mode of mechanical LiDARs wastes a significant amount of sensing resources on the useless background. Besides, the development of LiDAR hardware and software systems is currently split into two independent segments, lacking real-time interaction between physical entities and digital models in cyberspace. To address these issues, we propose software-defined active LiDARs for autonomous driving based on parallel intelligence. Active LiDARs redefine LiDAR's hardware operation through software systems to achieve adaptive sensing resource allocation, constituting a closed loop between physical space and cyberspace. During the working process, it calculates scenario heatmaps with the constructed high-definition maps (HD maps) in cyberspace at first. Then it takes prescriptive control of physical LiDARs based on heatmaps to improve sensing resource utilization. We build two adaptive LiDAR models in CARLA and construct a hardware prototype in the parallel sensing platform, DAWN. Active Point Cloud (APC), a new dataset collected in CARLA, is proposed and a 3D object detection task is selected to demonstrate the effectiveness of active LiDARs. Our experimental results show that active LiDARs can both improve raw data quality and model performance compared with mechanical LiDARs, especially for the perception of distant objects.
WOS关键词COMPLEX SCENES ; PERFORMANCE ; METAVERSES ; CHALLENGES ; PERCEPTION ; SYSTEMS ; VISION ; CPS
资助项目Key Research and Developing Program 2020 of Guangzhou[202007050002] ; Key-Area Research and Developing Program of Guangdong Province[2020B090921003] ; Intel Collaborative ResearchInstitute for Intelligent and Automated Connected Vehicles (ICRI-IACV)
WOS研究方向Computer Science ; Engineering ; Transportation
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:001075333800007
资助机构Key Research and Developing Program 2020 of Guangzhou ; Key-Area Research and Developing Program of Guangdong Province ; Intel Collaborative ResearchInstitute for Intelligent and Automated Connected Vehicles (ICRI-IACV)
源URL[http://ir.ia.ac.cn/handle/173211/53077]  
专题多模态人工智能系统全国重点实验室
通讯作者Shen, Yu
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
2.Beijing Huairou Acad Parallel Sensing, Beijing 101407, Peoples R China
3.North Automat Control Technol Inst, Taiyuan 030006, Peoples R China
4.Chinese Acad Sci, Inst Automat, Beijing Engn Res Ctr Intelligent Syst & Technol, Beijing 100190, Peoples R China
5.Univ Chinese Acad Sci, Dept Comp Sci & Technol, Beijing 100049, Peoples R China
6.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
7.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Liu, Yuhang,Sun, Boyi,Tian, Yonglin,et al. Software-Defined Active LiDARs for Autonomous Driving: A Parallel Intelligence-Based Adaptive Model[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2023,8(8):4047-4056.
APA Liu, Yuhang.,Sun, Boyi.,Tian, Yonglin.,Wang, Xingxia.,Zhu, Yin.,...&Shen, Yu.(2023).Software-Defined Active LiDARs for Autonomous Driving: A Parallel Intelligence-Based Adaptive Model.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(8),4047-4056.
MLA Liu, Yuhang,et al."Software-Defined Active LiDARs for Autonomous Driving: A Parallel Intelligence-Based Adaptive Model".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.8(2023):4047-4056.

入库方式: OAI收割

来源:自动化研究所

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