Electronics and Semiconductors

Nvidia leads self-driving car chip development progress

24 March 2020
Nvidia is developing semiconductors for autonomous vehicle technology and leading the way so far in 2020, according to Navigant Research. Source: Nvidia

Navigant Research has researched more than 70 companies to determine who is leading the charge in hardware for autonomous driving technology with Nvidia topping the list.

The research looked at three technologies required for the development of autonomous driving: sensors, software and computer platforms in the forms of central processing units (CPUs), field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs) and graphics processing units (GPUs). The report examined those companies that are developing compute platforms and have silicon designs at least in sample production. These systems must have fail-operational capabilities to ensure safety when there is no human backup.

Determining those companies leading the development process was based on 10 criteria: vision, go-to-market strategy, partners, production strategy, technology, sales, marketing and distribution, product capability, product quality and reliability, product portfolio and staying power. Of these attributes, Navigant found that Nvidia was the number one vendor in terms of automated driving chip development. This was due to Nvidia's history of producing strong hardware and software and a platform that meets ever-increasing performance and power efficiency.

Top 10 vendors include:

  1. Nvidia
  2. Intel-Mobileye
  3. Qualcomm Technologies
  4. Xilinx
  5. Waymo LLC
  6. Tesla
  7. NXP Semiconductors
  8. Renesas Electronics Corporation
  9. Apple Inc.
  10. AImotive

Nvidia specifically garnered praise for its Drive AGX platform, the scalable architecture and software designed to work with autonomous vehicle manufacturers' individual production plans.

According to Nvidia, compute chips are a critical element to self-driving cars that make it possible for these vehicles to process in real time the mass amount of data coming from cameras, radars and lidar sensors. These chips also help self-driving software run deep neural networks simultaneously, achieving the diversity and redundancy in operation that is critical for safety.

“As this technology evolves and matures, developers are going through many iterations of hardware and software,” said Sam Abuelsamid, principal research analyst at Navigant. “Having an ecosystem that allows you to develop at all different levels, from in-vehicle, to data center, to simulation and transfer knowledge you’ve gained from one to the other is very important.”

To learn more about Navigant’s self-driving car research, see its Navigant Research Leaderboard: Automated Vehicle Compute Platforms report.

To contact the author of this article, email PBrown@globalspec.com


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