Civil Maps now run on ARM family of processors

Civil Maps  has ported its vehicular cognition stack to run on the ARM family of processors. Arm is a licensor of automotive-grade system-on-chips (SoCs) and system-on-modules (SoMs), with more than 1,000 technology partners.

Self-driving car developers can leverage an Arm SoC with Civil Maps embedded software for enabling vehicles to navigate safely and localize on the road. Currently, no other competing solutions, which commonly rely on x86 and/or GPU-based architectures, offer developers a path to production-scale vehicle autonomy.

Sravan Puttagunta, CEO and Co-founder of Civil Maps said, “By reducing complexity, cost, in-car real estate, and power consumption, we are all now a step closer towards freedom from many of the systemic operational bottlenecks that have greatly encumbered AV development today.”

The Arm-powered HD maps and localization solution will enable greater levels of reliability and efficiency while overcoming chronic limitations of power consumption, CPU, storage, and network requirements. The timing of the transition coincides with the automotive industry’s overwhelming adoption of Arm technology for ECU that manage an expanding range of in-vehicle systems. Civil Maps’ migration means that OEMs will be able to leverage the company’s cutting-edge technology without changing their existing supply chain.

“Committing to an Arm-based architecture will greatly assist Civil Maps in seamlessly commercializing their technology to leading automakers,” said Tim Dawkins, Autonomous Car Specialist at SBD Automotive. “This approach will allow the OEMs and technology companies involved with autonomous development to implement a scalable localization platform with lean compute requirements.”

As part of the transition, Civil Maps has optimized core components of its algorithms and software for the Arm CPU architecture, known for its high-volume manufacturing process and auto-grade certifications. The efficiency of Civil Maps’ exclusive Fingerprint Base Map technology allows the company to leverage the Arm Neural Network accelerators in these low-power, low-cost SoCs.

Source: Civil Maps