Computing Technology in Autonomous Vehicle

The future of driving is quickly evolving toward AI-enabled, fully autonomous vehicles. The centralized Compute system will serve as a nerve center for all autonomous vehicles to meet stringent intelligence, performance, safety, security, and reliability requirements. We’re seeing the complexity of autonomous driving systems growing at an unprecedented rate, and computational processing needs to keep pace with this growth. A high-performance, automotive-grade Compute system must be able to accommodate numerous sensor inputs from cameras, radars, light detection and ranging radars (LiDAR), ultrasonic sensors, inertial sensor module (ISM), acoustic sensors, and Vehicle-to-Vehicle (V2V)/Vehicle-to-Everything (V2X) communications concurrently to accurately and reliably perceive the environment around the vehicles. Also, it must be able to promptly enable better and safer driving decisions including prediction, planning, and control after analyzing all the perceived information. In this chapter, motivations, as well as various, Compute architectures and key components consisting of an advanced autonomous vehicle Compute system such as System on Chip (SoC), memory, storage, and network are reviewed. Furthermore, real-time operating system, onboard management, fault detection and diagnostics, security, and middleware will be illustrated. How to conduct rigid electrical tests and reliability validation to qualify autonomous vehicle Compute will be covered. Finally, challenges in Compute design, manufacturing, and validation including performance, power consumption, thermal management, size, cost, safety, security, quality, and reliability are explored for safe deployment of the autonomous vehicle at scale.

The authors want to thank Dr. Daniel Braun from BMW Group for his critical reviews of this chapter.

Authors and Affiliations

1. Cruise LLC, San Francisco, CA, USA

   Fen Chen

2. Nio, San Jose, CA, USA

   Dong Zhao

Corresponding author

Correspondence to Fen Chen .

Editors and Affiliations

1. Intel Corporation, Chandler, AZ, USA

   Yan Li

2. Lyft, Palo Alto, CA, USA

   Hualiang Shi

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