Visibility is key to truck operation, that’s true for a human driver and it’s especially true for automated driving systems. While Level 2 self-driving technology (adaptive cruise control working with active lane keep assist) is available today, fully automated Level 4 machine driving requires even greater visibility. Visibility that might even be beyond what we see today.
So how do self-driving system see? And how can they identify what they’re looking at?
Enter Brad Rosen, chief operating officer, NODAR, provider of 3D vision technology that uses multiple cameras (aka stereo vision) independently mounted on the truck to provide long range, high resolution, real-time 3D sensing. Based on standard automotive-grade cameras that today ship in the billions of units/per year, these vision systems produce dense 3D point clouds with highly accurate distance estimates to each pixel, making the measurements that the camera senses more accurate.
Rosen gives us an overview of the technology being employed by automated systems today, what could be in store for solutions of tomorrow and what adoption of self-driving trucks could demand of the people who work with them. Watch the video above for all of the insight.
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