Software-Defined Active LiDARs for Autonomous Driving: A Parallel Intelligence-Based Adaptive Model

doi:10.1109/TIV.2023.3289540

	Software-Defined Active LiDARs for Autonomous Driving: A Parallel Intelligence-Based Adaptive Model
	Liu, Yuhang 1,2; Sun, Boyi 3; Tian, Yonglin4,5 ; Wang, Xingxia 1,2; Zhu, Yin 6; Huai, Rouxing 7; Shen, Yu1,2
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
ISSN	2379-8858
	2023-08-01
卷号	8 期号:8 页码:4047-4056
通讯作者	Shen, Yu(shenyu2015@ia.ac.cn)
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.
关键词	Software-defined active LiDARs parallel intelligence adaptive sensing resources allocation
DOI	10.1109/TIV.2023.3289540
关键词[WOS]	COMPLEX SCENES ; PERFORMANCE ; METAVERSES ; CHALLENGES ; PERCEPTION ; SYSTEMS ; VISION ; CPS
收录类别	SCI
语种	英语
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)
项目资助者	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)
WOS研究方向	Computer Science ; Engineering ; Transportation
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:001075333800007
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53078
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.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Univ Chinese Acad Sci, Dept Comp Sci & Technol, Beijing 100049, Peoples R China 4.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Chinese Acad Sci, Inst Automat, Beijing Engn Res Ctr Intelligent Syst & Technol, Beijing 100190, Peoples R China 6.North Automat Control Technol Inst, Taiyuan 030006, Peoples R China 7.Beijing Huairou Acad Parallel Sensing, Beijing 101407, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
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.