Cameras, radar and even humans help to keep autonomous vehicles safe. The three complement each other. Cameras are cheap and can see street signs and road markings, but cannot measure distance; radar can measure distance and velocity, but cannot see in fine detail; LIDAR provides fine detail but is expensive and gets confused by snow.
Most people working on autonomous vehicles believe a combination of sensors is needed to ensure safety and reliability. Having combined the data from its sensors, the car needs to identify the items around it: other vehicles, pedestrians, cyclists, road markings, road signs and so forth.
Humans are much better at this than machines, which have to be trained with lots of carefully labelled examples. One way to obtain them is to pay people to label images manually. Mighty AI, based in Seattle, has an online community of , people who carefully label images of street scenes, drawing boxes around cars, trees and so forth, for a range of automotive clients. The labelled images are then used to train vision systems used in autonomous cars.
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The hardest things to identify are rarely seen items such as debris on the road or plastic bags blowing across a highway. Puddles on the road also caused confusion.
Combining data from multiple sensors, however, can reveal whether an item in the road is a solid obstacle or not. That may give an edge to first movers who have already racked up thousands or millions of miles of self-driving experience—and the associated gigabytes of driving data.
The novel Kaleidoscope of Life concerns the lives of Sally Evans, her immediate and extended families, and those of the local aborigines entwined throughout. See All Customer Reviews. Without it there would have been no outs with runners on the corners and Patrick Corbin nearing the end of his start. Showing The three complement each other.
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