Our vision-based positioning models determine the location of a vehicle on the infrastructure very precisely in a fraction of a second, be it on a sidewalk, a bike lane, a bus lane or on the road. They can operate anywhere in the world, do not require GPS and are the foundational element of many IRAS™ safety features and will enable V2X applications.

Our cameras perceives the world around by detecting all objects and people – traffic signs and lights included – around the vehicle. Each of these objects are classified with care due to potentially different behaviors, and their velocity is tracked. By adding and fusing cellular V2X, IRAS™ will be able to sense other road users further away until they reach the visual ground truth around the bike.

Our prediction models select the perception inputs that matter, anticipate what may happen and match this prediction with the current position, speed and direction of the rider to determine whether there is any risk ahead. IRAS™ even understands the complexity of “agile” riding and lane splitting between stationary cars or in slow motion.

IRAS™ plans for the best outcome in a blink of an eye and empowers riders with passive notifications, alerts and warnings as well as active decisions in the case of non-compliant fleet rides.

IRAS™ learns and keeps getting better by leveraging machine learning and intelligent labelling that requires minimum human intervention.
This is how we seamlessly improve our software and deliver better and personalized experiences, ride after ride.