Development and Testing of Advanced Driver Assistance Systems Through Scenario-Based Systems Engineering

doi:10.1109/TIV.2023.3297168

	Development and Testing of Advanced Driver Assistance Systems Through Scenario-Based Systems Engineering
	Li, Xuan 1; Song, Rui 2,3; Fan, Junfeng4 ; Liu, Mingyang5 ; Wang, Fei-Yue4
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
ISSN	2379-8858
	2023-08-01
卷号	8 期号:8 页码:3968-3973
通讯作者	Fan, Junfeng(junfeng.fan@ia.ac.cn) ; Wang, Fei-Yue(feiyue@ieee.org)
摘要	Advanced driver assistance systems (ADAS) hold great promise for improving transportation safety and efficiency. However, the development of these technologies requires a robust and systematic engineering process to ensure their reliable and safe operation in various traffic situations. In this letter, we present a scenario-based systems engineering for the development and test of advanced driver assistance systems, drawing insights from a real automotive proving ground. This letter is the second part of Decentralized and Hybrid Workshop (DHW) on Scenarios Engineering (SE), which aims to improve scenario diversity and representation for advanced driver assistance systems. The article proposes a 5-layer scenario architecture and also describes several key tasks that must be addressed in the ADAS, such as lane keeping assistance (LSK), adaptive cruise control (ACC) and autonomous emergency braking (AEB). Additionally, we elaborate on the testing challenges that the aforementioned tasks entail. Finally, we employ clustering methods to obtain 9 crucial scenarios of LKA, which can be utilized for ADAS testing.
关键词	Roads Testing Vehicles Systems engineering and theory Advanced driver assistance systems Meters Autonomous vehicles Scenarios-based system engineering advanced driver assistance systems parallel intelligence lane keeping assistance adaptive cruise control autonomous emergency braking
DOI	10.1109/TIV.2023.3297168
关键词[WOS]	INTELLIGENT VEHICLES ; VALIDATION
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62203250] ; National Natural Science Foundation of China[62003341] ; Young Elite Scientists Sponsorship Program of China Association of Science and Technology[YESS20210289] ; China Postdoctoral Science Foundation[2020TQ1057] ; China Postdoctoral Science Foundation[2020M682823] ; Beijing Natural Science Foundation[4232057] ; Youth Innovation Promotion Association of CAS[2022130]
项目资助者	National Natural Science Foundation of China ; Young Elite Scientists Sponsorship Program of China Association of Science and Technology ; China Postdoctoral Science Foundation ; Beijing Natural Science Foundation ; Youth Innovation Promotion Association of CAS
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:001075333800002
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：4[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/173211/53015
专题	多模态人工智能系统全国重点实验室
通讯作者	Fan, Junfeng; Wang, Fei-Yue
作者单位	1.Peng Cheng Lab, Shenzhen 518000, Peoples R China 2.Changan Univ, Sch Informat Engn, Xian 710064, Peoples R China 3.China Automot Technol Res Ctr Co Ltd, Tianjin 300300, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Guangzhou Co Ltd, CATARC Automot Test Ctr, Guangzhou 511300, Peoples R China
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	Li, Xuan,Song, Rui,Fan, Junfeng,et al. Development and Testing of Advanced Driver Assistance Systems Through Scenario-Based Systems Engineering[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2023,8(8):3968-3973.
APA	Li, Xuan,Song, Rui,Fan, Junfeng,Liu, Mingyang,&Wang, Fei-Yue.(2023).Development and Testing of Advanced Driver Assistance Systems Through Scenario-Based Systems Engineering.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(8),3968-3973.
MLA	Li, Xuan,et al."Development and Testing of Advanced Driver Assistance Systems Through Scenario-Based Systems Engineering".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.8(2023):3968-3973.