Terranet Demos 3D AD/ADAS Sensor Technology

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Source: Terranet AB announcement

LUND, Sweden – Terranet AB (Nasdaq: TERRNT-B.ST), developers of advanced driver-assistance software that specifically addresses safety, successfully showcased its patented, VoxelFlow™ sensor technology at STARTUP AUTOBAHN yesterday in a joint presentation with Mercedes-Benz.

VoxelFlow™ uses high speed sensor technology so that autonomous driving (AD) and advanced driver-assistance systems (ADAS) can quickly and accurately understand and decipher what is in front of them, enhancing existing radar, lidar and camera systems that particularly struggle within 30 to 40 meters, when an accident is most likely to take place.

At STARTUP AUTOBAHN, Terranet displayed how its lightning-fast 3D technology, VoxelFlow™ scans an area with a radius of 40 meters around the vehicle and reacts in three milliseconds. Through a project between Mercedes-Benz and Terranet, the VoxelFlow™ Sensor Data was fed into a safety map for Mercedes-Benz’s navigation system “LiveMap,” which is updated in real-time.

Together, the two technologies will be able to dynamically perceive moving objects and subsequently recognize events and hazard spots. Ultimately the partnership between Terranet and Mercedes-Benz will drastically improve the overall navigation experience and make all our roads safer.

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VoxelFlow™ is a solid state system that will allow AD/ADAS vehicles to perceive the world in 3D voxels, a stark contrast to today’s 2D pixel-based vision systems. Currently, VoxelFlow™ processes an astounding 250,000 voxels per second.

By the end of 2021, Terranet expects the groundbreaking sensor technology to process over a million voxels, giving driving automation systems the ability to navigate roadways using 3D data points. On its way to becoming an industry-standard sensor system, VoxelFlow™ will enhance existing radar, lidar and camera systems, that especially struggle in inclement weather.

“Scandinavia has a rich history in bringing world changing safety measures to the automotive industry, and Terranet is continuing down that road with our VoxelFlow technology,” said Terranet CEO, Pär-Olof Johannesson. “Roadway related incidents are the eighth leading cause of death globally. We are not going to cut down that harrowing statistic by using existing laser technology suited for long-range use and hoping we can ‘make it work’ on the average vehicle. If the driving automation industry wants to start taking safety seriously, we need to start embracing 3D vision and technology designed specifically with roadway vehicles in mind.”

VoxelFlow™ consists of three event cameras and a continuous laser scanner, whose simultaneous observations use triangulation to generate a 3D image within a matter of nanoseconds.The system is able to detect, track and trace that 3D image, in addition to specifying velocity, speed, direction and position. Unmatched in its field, VoxelFlow™ will generate the best way to perceive motion of 3D objects in space, creating a new way of seeing within the automotive industry.

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The system cuts the reaction distance from six metres to six centimetres and will be 10 times faster than existing technology. By significantly cutting down response time and generating an authentic view of the world around the vehicle, VoxelFlow™ will help ensure the safety of all those on the roadways.

At 250,000 voxels per second, VoxelFlow is already matching competitors in point density. Where current camera/laser technology is subject to delays in latency or deficiencies in image quality, VoxelFlow™ creates high-resolution, low latency images, moving beyond pixels to reimagine the world in voxels. Sensor technology designed specifically with AD/ADAS vehicles in mind, VoxelFlow’s™ low latency caters to object detection within 30-40 meters. Further, VoxelFlow™ shortens the braking distance significantly when the vehicle is travelling at 70 km/h. Further the hybrid event-based camera and laser approach, allows VoxelFlow™ to work across all forms of weather and during every time of day.

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