TY - GEN
T1 - Design Automation for Intelligent Automotive Systems
AU - Lan, Shuyue
AU - Huang, Chao
AU - Wang, Zhilu
AU - Liang, Hengyi
AU - Su, Wenhao
AU - Zhu, Qi
N1 - Funding Information:
This work is supported partially by the National Science Foundation grants CNS-1839511, CCF-1834701, CCF-1834324, and IIS-1724341.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - With rapid advancement of advanced driver assistance systems (ADAS) and autonomous driving functions, modern vehicles have become ever more intelligent than before. Sophisticated machine learning techniques have being developed for vehicle perception, planning and control. However, this also brings significant challenges to the design, implementation and validation of automotive systems, stemming from the fast-growing functional complexity, the adoption of advanced architectural components such as multicore CPUs and GPUs, the dynamic and uncertain physical environment, and the stringent requirements on various system metrics such as safety, security, reliability, performance, fault tolerance, extensibility, and cost. To address these challenges, new design methodologies, algorithms and tools are greatly needed. This paper will discuss the challenges in designing next-generation connected and autonomous vehicles, and the need of design automation techniques to tackle them.
AB - With rapid advancement of advanced driver assistance systems (ADAS) and autonomous driving functions, modern vehicles have become ever more intelligent than before. Sophisticated machine learning techniques have being developed for vehicle perception, planning and control. However, this also brings significant challenges to the design, implementation and validation of automotive systems, stemming from the fast-growing functional complexity, the adoption of advanced architectural components such as multicore CPUs and GPUs, the dynamic and uncertain physical environment, and the stringent requirements on various system metrics such as safety, security, reliability, performance, fault tolerance, extensibility, and cost. To address these challenges, new design methodologies, algorithms and tools are greatly needed. This paper will discuss the challenges in designing next-generation connected and autonomous vehicles, and the need of design automation techniques to tackle them.
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U2 - 10.1109/TEST.2018.8624723
DO - 10.1109/TEST.2018.8624723
M3 - Conference contribution
AN - SCOPUS:85062383691
T3 - Proceedings - International Test Conference
BT - International Test Conference 2018, ITC 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 49th IEEE International Test Conference, ITC 2018
Y2 - 29 October 2018 through 1 November 2018
ER -