Energy Efficient Computing R&D Roadmap Outline for Automated Vehicles
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Archive
- Carnegie Mellon Univ., Pittsburgh, PA (United States)
- Hewlett Packard Enterprise, Houston, TX (United States)
- Intel, Mountain View, CA (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Univ. of Michigan, Ann Arbor, MI (United States)
Automated vehicles (AV) hold great promise for improving safety, as well as reducing congestion and emissions. In order to make automated vehicles commercially viable, a reliable and highperformance vehicle-based computing platform that meets ever-increasing computational demands will be key. Given the state of existing digital computing technology, designers will face significant challenges in meeting the needs of highly automated vehicles without exceeding thermal constraints or consuming a large portion of the energy available on vehicles, thus reducing range between charges or refills. The accompanying increases in energy for AV use will place increased demand on energy production and distribution infrastructure, which also motivates increasing computational energy efficiency.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- NA0003525
- OSTI ID:
- 1821804
- Report Number(s):
- SAND2021-10210R; 699831
- Country of Publication:
- United States
- Language:
- English
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