Next Generation Automotive Architecture Modeling and Exploration for Autonomous Driving

被引:23
作者
Zheng, Bowen [1 ]
Liang, Hengyi [1 ]
Zhu, Qi [1 ]
Yu, Huafeng [2 ]
Lin, Chung-Wei [2 ]
机构
[1] Univ Calif Riverside, Riverside, CA 92521 USA
[2] TOYOTA InfoTechnol Ctr, Mountain View, CA 94043 USA
来源
2016 IEEE COMPUTER SOCIETY ANNUAL SYMPOSIUM ON VLSI (ISVLSI) | 2016年
关键词
D O I
10.1109/ISVLSI.2016.126
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:53 / 58
页数:6
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