Yandex notes that it has navigation, geolocation, computer vision, and machine learning expertise from other ongoing products and services, including Yandex.Navigator and Yandex.Maps.
"We use anonymised data that we receive from Yandex.Navigator users, which allows us to understand how to drive in a city with its traffic congestion, accidents, speed limits, road closures and other traffic events," Yandex.Taxi Head of PR Vladimir Isaev explained via email. "We have been using computer vision technologies in a number of our services for quite a while. We use them to find vacant parking spaces or read road signs, for instance, in our geolocation services."
Expertise with computer vision use at Yandex comes from matching similar images for search results, and for translating text within a photo through its language service offerings. As a result of its combined software development efforts, as well as recent work on applying said tech to the automotive space, Yandex's self-driving software for its prototype vehicle is developed completely in house, the company tells me.
Also, you may have noticed the lingering shot on that Nvidia GTX GPU in the car, as well as that Velodyne LiDAR unit up top: Yandex says it's using its own "custom-built" hardware as well as mass market, generally available components for now, but it's in talks with partners regarding the creation of fit-for-purpose automotive grade hardware down the road.
The vehicle in the video isn't yet navigating real city streets, but Yandex says that testing is coming on public roads within a year, if all goes as planned. It's too early yet for any projections regarding commercial service availability, however, Isaev tells me. Eventually, the company hopes to partner with car manufacturers and others looking to bring autonomous vehicles to market.
This article by Darrell Etherington originally appeared on TechCrunch.