Design Automation for Intelligent Automotive Systems

Shuyue Lan, Chao Huang, Zhilu Wang, Hengyi Liang, Wenhao Su, Qi Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish (US)
Title of host publicationInternational Test Conference 2018, ITC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538683828
DOIs
StatePublished - Jan 23 2019
Event49th IEEE International Test Conference, ITC 2018 - Phoenix, United States
Duration: Oct 29 2018Nov 1 2018

Publication series

NameProceedings - International Test Conference
Volume2018-October
ISSN (Print)1089-3539

Conference

Conference49th IEEE International Test Conference, ITC 2018
CountryUnited States
CityPhoenix
Period10/29/1811/1/18

Fingerprint

Design Automation
Automation
Metric unit
Driver Assistance
Autonomous Vehicles
Fault Tolerance
Advanced driver assistance systems
Metric system
Design Methodology
Machine Learning
Safety
Planning
Fault tolerance
Program processors
Learning systems
Requirements
Costs
Perception
Design
Architecture

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Lan, S., Huang, C., Wang, Z., Liang, H., Su, W., & Zhu, Q. (2019). Design Automation for Intelligent Automotive Systems. In International Test Conference 2018, ITC 2018 - Proceedings [8624723] (Proceedings - International Test Conference; Vol. 2018-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TEST.2018.8624723
Lan, Shuyue ; Huang, Chao ; Wang, Zhilu ; Liang, Hengyi ; Su, Wenhao ; Zhu, Qi. / Design Automation for Intelligent Automotive Systems. International Test Conference 2018, ITC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - International Test Conference).
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Lan, S, Huang, C, Wang, Z, Liang, H, Su, W & Zhu, Q 2019, Design Automation for Intelligent Automotive Systems. in International Test Conference 2018, ITC 2018 - Proceedings., 8624723, Proceedings - International Test Conference, vol. 2018-October, Institute of Electrical and Electronics Engineers Inc., 49th IEEE International Test Conference, ITC 2018, Phoenix, United States, 10/29/18. https://doi.org/10.1109/TEST.2018.8624723

Design Automation for Intelligent Automotive Systems. / Lan, Shuyue; Huang, Chao; Wang, Zhilu; Liang, Hengyi; Su, Wenhao; Zhu, Qi.

International Test Conference 2018, ITC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8624723 (Proceedings - International Test Conference; Vol. 2018-October).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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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Lan S, Huang C, Wang Z, Liang H, Su W, Zhu Q. Design Automation for Intelligent Automotive Systems. In International Test Conference 2018, ITC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8624723. (Proceedings - International Test Conference). https://doi.org/10.1109/TEST.2018.8624723