[usrusr]

So it's like the radar-based Garmin RTL5xx (née Backtracker) but with the added benefit of "hit or pass" lane information and all the warning escalation you can do with that. I'm generally extremely sceptical of technical solutions to driver inventiveness (they will eventually out-risk-compensate everything you throw at them, it's a one-sided arms race) but they might be on to something here. The Garmin is already surprisingly popular and proper use of lateral information would greatly add to the appeal. A contender for the annual Garmin Fitness acquisition 2021 perhaps?

edit: Still, I'd be afraid that falls from startled reactions by the cyclists themselves might in the end cause more bloodshed than the extremely rare rear-ender it's supposed to prevent. A car preparing a well timed overtake (close in fast inside the lane to sweep left just after oncoming traffic passes) will be a false positive you can't avoid without directly guessing intention and skill of the driver. It will surely be a net-positive in some communities with particularly low cyclist awareness amongst drivers but not necessarily in others.

[Luxonis-Brandon]

Thanks for the comments usrusr! And great points. So one of the things we did early-on is to prototype the whole flow to see if you could indeed get incredibly low false-positives. The key ended up being the combination of disparity depth (which gives over 1 million depth points) and neural inference so that the system can know incredibly granularly (i.e. within inches) the edges of things and their predictive trajectories.

So at the outset of this effort (back in 2017) such a computer-vision based device that was inexpensive and embeddable was impossible. The Movidius Myriad X came out, which has all the requisite CV/AI processing to make such a thing solvable... but there was no hardware/firmware/software/AI ecosystem which allowed producing such embedded spatial AI problems.

So we had to build that first to solve this safety problem and we're releasing it in conjunction with OpenCV as the OpenCV AI Kit (OAK). https://opencv.org/opencv-spatial-ai-competition/

So the `why` of this is it allows others to solve problems on embedded systems which were previously intractable. And there are a ton of them... the number of applications we've seen has blown our mind.

We'll have a KickStarter around this OpenCV AI Kit which will be going live on July 14th: https://www.kickstarter.com/projects/opencv/opencv-ai-kit

Thoughts?

Thanks, Brandon