Terranet self-driving sensor tests show swift reaction time
21/07/2021 13:00
By Nick Carey
LONDON, July 21 (Reuters) - Self-driving car technology
developer Terranet TERRNTb.ST said on Wednesday that tests of
its sensor system have shown a dramatic improvement in reaction
time to objects in the road, which should help cars brake faster
and reduce accidents.
The startup has been conducting tests on a Mercedes-Benz car
in partnership with Daimler AG DAIGn.DE .
Terranet said the tests showed its 3D motion awareness
technology, called VoxelFlow, could identify and react to
objects in or alongside the road in less than 20 milliseconds,
far faster than the 300 milliseconds common for the Advanced
Driver Assistance Systems (ADAS) available in systems today.
Chief Technology Officer Nihat Küçük, a former Mercedes-Benz
executive, said the system used artificial intelligence to
quickly identify an object, whether a plastic bag blowing in the
wind or a child running between parked cars, and prepared to
brake if there was a safety risk.
"We can't cheat physics and reduce braking distance at
speeds, but we can reduce the reaction time before braking,"
Küçük said, adding that the company was talking to other
carmakers and auto suppliers about building prototypes to test
the technology.
Automakers are pushing to develop self-driving cars, but
this poses significant challenges, especially getting vehicles
to mimic the complexity of the human brain in recognising and
reacting to objects in the road at high speeds.
Many automakers have focused on light detection and ranging
(lidar) sensors, using laser light pulses to render precise
images of the environment around the car, to develop higher
levels of driver assistance on the fully self-driving vehicles.
VoxelFlow consists of three event cameras and a continuous
laser scanner to create a 3D image of the road ahead.
Küçük said lidar was better suited to highway driving but
Terranet's system was designed for more urban, crowded areas
where a swift reaction time is needed to avoid pedestrians and
cars.
(Reporting by Nick Carey; Editing by Edmund Blair)
((nick.carey@thomsonreuters.com; +44 7385 414 954;))