MetaScenario: A Framework for Driving Scenario Data Description, Storage and Indexing

doi:10.1109/TIV.2022.3215503

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	MetaScenario: A Framework for Driving Scenario Data Description, Storage and Indexing
	Chang, Cheng 6; Cao, Dongpu 8; Chen, Long 7; Su, Kui 9; Su, Kuifeng ; Su, Yuelong 10; Wang, Fei-Yue 1,2; Wang, Jue ; Wang, Ping 3; Wei, Junqing 4
刊名	IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
	2023-02-01
卷号	8 期号:2 页码:1156-1175
关键词	Cameras Laser radar Autonomous vehicles Roads Annotations Trajectory Indexing Driving scenario data storage data indexing
ISSN号	2379-8858
DOI	10.1109/TIV.2022.3215503
通讯作者	Li, Li(li-li@tsinghua.edu.cn)
英文摘要	Autonomous driving related researches require the analysis and usage of massive amounts of driving scenario data. Compared to raw data collected by sensors, scenario data provide a preliminary abstraction of driving tasks and processes, explicitly integrate information about the road environment and the dynamic and static attributes of traffic participants, making it easier to conduct task understanding and decision making. However, many existing driving scenario datasets have the following two problems. First, it is not clear which data fields need to be recorded for driving scenarios. The data storage formats and organization standards are inconsistent. Second, the datasets cannot establish driving scenario indexing effectively. Existing datasets are sparsely annotated and difficult to index, which is detrimental to data sampling and extraction for machine learning process, thus hindering efficient fusion and reuse. In this paper, we propose MetaScenario, a framework for driving scenario data. We describe driving scenarios and design the centralized and unified data framework for the storage, processing, and indexing of scenario data based on relational database. The concept of atom scenario is proposed and characterized using semantic graphs. We also annotate and classify behaviors and interactions of traffic participants in atom scenarios by extracting the spatiotemporal evolution of semantic information. The annotation facilitates the indexing and extraction of data. The scenario datasets are further evaluated via the data distribution and annotation statistics. MetaScenario can provide researchers with convenient tools for scenario data extraction and important analytical references.
资助项目	National Key Research and Development Program of China[2020AAA0108104] ; Science and Technology Innovation Committee of Shenzhen[CJGJZD20200617102801005]
WOS关键词	CLASSIFICATION ; INTELLIGENCE ; STRATEGY ; VEHICLES
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:000967428300001
资助机构	National Key Research and Development Program of China ; Science and Technology Innovation Committee of Shenzhen
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53744]
专题	多模态人工智能系统全国重点实验室
通讯作者	Li, Li
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Qingdao Acad Intelligent Ind, Qingdao 266000, Peoples R China 3.Peking Univ, Beijing 100084, Peoples R China 4.DiDi Autonomous Driving Co, Beijing 100094, Peoples R China 5.Tsinghua Univ, Dept Automat, BNRist, Beijing 100084, Peoples R China 6.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China 7.Waytous Inc, Beijing 100083, Peoples R China 8.Univ Waterloo, Dept Mech & Mechatron Engn, Waterloo, ON N2L 3G1, Canada 9.Alibaba DAMO Acad Autonomous Driving Lab, Hangzhou 311121, Peoples R China 10.AutoNavi Software Co, Traff Management Solut Div, Beijing 100102, Peoples R China
推荐引用方式 GB/T 7714	Chang, Cheng,Cao, Dongpu,Chen, Long,et al. MetaScenario: A Framework for Driving Scenario Data Description, Storage and Indexing[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2023,8(2):1156-1175.
APA	Chang, Cheng.,Cao, Dongpu.,Chen, Long.,Su, Kui.,Su, Kuifeng.,...&Li, Li.(2023).MetaScenario: A Framework for Driving Scenario Data Description, Storage and Indexing.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(2),1156-1175.
MLA	Chang, Cheng,et al."MetaScenario: A Framework for Driving Scenario Data Description, Storage and Indexing".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.2(2023):1156-1175.