As autonomous vehicles make their way onto our roads, Manuel del Castillo, VP Business Development, Focal Point Positioning writes how GNSS is integral
Automotive OEMs can successfully navigate the transition from Level 2 to Level 3 automation by leveraging advanced GNSS solutions that deliver the positioning reliability necessary for the next generation of autonomous vehicles.
A major transformation in the automotive industry today is the progression toward higher levels of vehicle automation. This evolution is centered on Advanced Driver Assistance Systems (ADAS), which lay the foundation for autonomous capabilities that promise unprecedented safety, efficiency, and convenience improvements.
As automotive manufacturers transition from Level 2 (partial automation) to Level 3 (conditional automation), positioning reliability becomes increasingly crucial. What do we mean by positioning reliability? It is the ability to consistently deliver good positioning accuracy, even in challenging environments.
There has been a fundamental shift in the way cars interact and make decisions in response to their environment.
Global Navigation Satellite System (GNSS) is the primary source of absolute location data in this transition. Positioning systems currently meet Level 2 automation requirements, but Level 3 demands significantly higher reliability, regardless of the operating environment. It is remarkable how much GNSS reliability improvement can be achieved through simply enhancing the chip’s software, allowing ADAS to function effectively in traditionally challenging environments.
It is predicted that by 2030, up to 10% of global new car sales could be Level 3 vehicles.
Mercedes-Benz has developed a Level 3 system called Drive Pilot, which allows drivers to take their eyes off the road under certain conditions. In 2024, BMW became the first manufacturer to use a combination of Level 2 and Level 3 automated driving systems.
Leveraging the power of GNSS as a source of reliable absolute location is vital. It not only provides a crucial independent location cross-check, but it also accelerates system initialisation by giving HD maps a reference starting point, reducing computational load and improving efficiency. Additionally, GNSS aids in sensor calibration, correcting drift in IMUs and MEMS sensors over time. As a result, beyond traditional navigation, GNSS is a foundational technology for automation, supporting key functions across positioning, location-based services, ADAS, and automated driving systems.
A reliable GNSS receiver is set to play an important role as a component of the ADAS system, as it has the unique ability to provide a reliable source of absolute location. However, it suffers degradation in urban areas and under foliage, due to signal interference from buildings, trees and other obstacles, limiting its potential as an ADAS component.
FocalPoint has solved this challenge with software that enhances the accuracy and reliability of GNSS in these challenging environments.
The technology measures the direction of incoming signals, allowing the receiver to focus on line-of-sight signals while ignoring all other signal components. This approach mitigates multipath interference and blocks spoofing attempts. By improving sensitivity of the receiver to line-of-sight signals, it also optimises GNSS performance under tree cover, or when using antennas in sub-optimal placements. The result is enhanced reliability in scenarios where conventional GNSS struggles.
To obtain vital insight into the challenges and solutions for automotive OEMs on the road to Level 3 autonomy, download the FocalPoint whitepaper, ‘Navigating from Level 2 to Level 3 autonomy: Reliable GNSS as a key enabler of driving automation’.
Manuel Del Castillo is VP at FocalPoint, leading Business Development in the automotive, wearables and smartphone sectors. He holds an MBA in Business Administration, an MSc in Telecommunications Engineering and has over 20 years’ experience in the GNSS industry, having previously worked for semiconductor manufacturer Broadcom.
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