While the idea of a future where we all zip around in self-driving vehicles while drinking coffee or catching a pre-work nap is enticing even to the motorcycling-obsessed Ride Vision staff, it’s likely much farther away than we think.
What are Advanced Rider Assistance Systems and why is it so difficult to build one that both works and loved by riders?
Riders are very aware of the dangers of riding on the road. According to a recent study by the Insurance Information Institute, motorcycle riders are 29 times more likely to be involved in a fatal roadway accident than automotive passengers are.
When considering the various aspects of a motorcycle ride, one usually thinks about riding in different and various levels of traffic ranging from empty roads, through low level traffic that is all going the same way as the rider, and up to stand-still traffic that is many times associated with rush hours.
Ride Vision’s testing team uses several motorcycles from different makers. They ride on public roads in daily traffic which ranges from empty roads to heavy traffic. Back at the office, the team pulls and inspects the recorded footage from the system. A few days ago, as the team replayed that day’s footage, they saw an incident that happened in front of the test bike and was caught on the video.
Ride Vision’s system utilizes standard wide angle cameras with a fusion of computer vision & deep learning algorithms on the edge to predict and alert on upcoming collisions, without disturbing riders’ focus. Ride Vision’s system effectively helps riders to combine both the fixed and the peripheral visions, by tracking almost 360° around a motorcycle.
Ride Vision’s Threat Analysis learns and deducts patterns of motorcycle behaviors on the road and constantly blends and fuses all the data points to infer instantly whether any threat can emerge.
What if the motorcycles, and their riders, could be enhanced by the Predictive Vision of machines? Powered by the Predictive Vision of Artificial Intelligence (AI) and Computer Vision, motorcycles will extend the rider’s vision to predict 360 degree threats and help them enjoy the ride…