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ADAS & Autonomous Vehicle International
Trucks

Plus to use Aeva 4D lidar in commercially available truck systems

Lawrence ButcherBy Lawrence ButcherNovember 19, 20212 Mins Read
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Plus (formerly Plus.ai), a developer of self-driving truck technology, has selected Aeva to supply automotive-grade long-range 4D lidar for its driver-in and fully autonomous trucks.

Aeva and Plus have been collaborating since 2019 to equip and validate Plus’s autonomous trucking system with Aeva Frequency Modulated Continuous Wave (FMCW) 4D lidar. Following the recent agreement, Plus will now use Aeva’s 4D lidar sensors to augment the long-range perception in its commercially available driver-in product starting in late 2022.

Production and delivery of the PlusDrive driver-in autonomous trucking solution to customers began in early 2021, with plans for more than 100,000 vehicles to be in service by the end of 2025. The PlusDrive solution is designed for fleets that are looking to improve driver retention, enhance safety, reduce fuel costs and lower their carbon emissions.

“Our global deployment of automated trucks to fleets commercially at scale requires leading technology that is automotive grade, high performance and practical. We selected Aeva as our production partner because its 4D lidar complements Plus’s state-of-the-art long-range perception by adding important instant velocity detection for the safe operation of autonomous trucks, and Aeva shares our commitment to bring autonomous trucks to market,” said Shawn Kerrigan, COO and co-founder of Plus.

Heavy trucks take much longer to stop than passenger cars. Therefore, an automated trucking sensor system needs to detect objects, place them in lanes and assign an accurate velocity at very long ranges. Aeva’s 4D lidar is claimed to sense precise velocity and position for each point, even at distances of over 500m. According to Plus, the combination of 4D lidar with its proprietary autonomy stack addresses many edge cases, such as previously unseen obstacles that may confound deep neural networks in the perception stack.

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