Next generation automotive architecture modeling and exploration for autonomous driving

Bowen Zheng, Hengyi Liang, Qi Zhu, Huafeng Yu, Chung Wei Lin

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

12 Scopus citations

Abstract

To support emerging applications in autonomous and semi-autonomous driving, next-generation automotive systems will be equipped with an increasing number of heterogeneous components (sensors, actuators and computation units connected through various buses), and have to process a high volume of data to percept the environment accurately and efficiently. Challenges for such systems include system integration, prediction, verification and validation. In this work, we propose an architecture modeling and exploration framework for evaluating various software and hardware architecture options. The framework will facilitate system integration and optimization, and enable validation of various design metrics such as timing, reliability, security and performance.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016
PublisherIEEE Computer Society
Pages53-58
Number of pages6
Volume2016-September
ISBN (Electronic)9781467390385
DOIs
StatePublished - Sep 2 2016
Event15th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016 - Pittsburgh, United States
Duration: Jul 11 2016Jul 13 2016

Other

Other15th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016
CountryUnited States
CityPittsburgh
Period7/11/167/13/16

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Next generation automotive architecture modeling and exploration for autonomous driving'. Together they form a unique fingerprint.

Cite this