Abstract
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.
Original language | English (US) |
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Title of host publication | International Test Conference 2018, ITC 2018 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538683828 |
DOIs | |
State | Published - Jul 2 2018 |
Event | 49th IEEE International Test Conference, ITC 2018 - Phoenix, United States Duration: Oct 29 2018 → Nov 1 2018 |
Publication series
Name | Proceedings - International Test Conference |
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Volume | 2018-October |
ISSN (Print) | 1089-3539 |
Conference
Conference | 49th IEEE International Test Conference, ITC 2018 |
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Country/Territory | United States |
City | Phoenix |
Period | 10/29/18 → 11/1/18 |
Funding
This work is supported partially by the National Science Foundation grants CNS-1839511, CCF-1834701, CCF-1834324, and IIS-1724341.
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Applied Mathematics