Next generation automotive architecture modeling and exploration for autonomous driving

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

doi:10.1109/ISVLSI.2016.126

Next generation automotive architecture modeling and exploration for autonomous driving

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

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

20 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 language	English (US)
Title of host publication	Proceedings - IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016
Publisher	IEEE Computer Society
Pages	53-58
Number of pages	6
Volume	2016-September
ISBN (Electronic)	9781467390385
DOIs	https://doi.org/10.1109/ISVLSI.2016.126
State	Published - Sep 2 2016
Event	15th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016 - Pittsburgh, United States Duration: Jul 11 2016 → Jul 13 2016

Other

Other	15th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016
Country/Territory	United States
City	Pittsburgh
Period	7/11/16 → 7/13/16

ASJC Scopus subject areas

Hardware and Architecture
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ISVLSI.2016.126

Cite this

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title = "Next generation automotive architecture modeling and exploration for autonomous driving",

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.",

author = "Bowen Zheng and Hengyi Liang and Qi Zhu and Huafeng Yu and Lin, {Chung Wei}",

year = "2016",

month = sep,

day = "2",

doi = "10.1109/ISVLSI.2016.126",

language = "English (US)",

volume = "2016-September",

pages = "53--58",

booktitle = "Proceedings - IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016",

publisher = "IEEE Computer Society",

address = "United States",

note = "15th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016 ; Conference date: 11-07-2016 Through 13-07-2016",

}

Zheng, B, Liang, H, Zhu, Q, Yu, H & Lin, CW 2016, Next generation automotive architecture modeling and exploration for autonomous driving. in Proceedings - IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016. vol. 2016-September, 7560172, IEEE Computer Society, pp. 53-58, 15th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016, Pittsburgh, United States, 7/11/16. https://doi.org/10.1109/ISVLSI.2016.126

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AU - Zheng, Bowen

AU - Liang, Hengyi

AU - Zhu, Qi

AU - Yu, Huafeng

AU - Lin, Chung Wei

PY - 2016/9/2

Y1 - 2016/9/2

N2 - 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.

AB - 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.

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M3 - Conference contribution

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VL - 2016-September

SP - 53

EP - 58

BT - Proceedings - IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016

PB - IEEE Computer Society

T2 - 15th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2016

Y2 - 11 July 2016 through 13 July 2016

ER -

Next generation automotive architecture modeling and exploration for autonomous driving

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