AUTONOMOUS & CONNECTED VEHICLES
Validating correct behavior in ADAS and AV systems Autonomous vehicles must operate in a world of uncertainties. Validation platforms are now capable of determining whether behavior is correct given complex contextual attributes.
There is an interesting dashcam video circulating in the autonomous vehicle (AV) development community of a Tesla-paid test driver coming up on what the driver calls the curve of death. He has gone through this particular curve numerous times with the autopilot feature turned on. In the video, the car starts out driving too close to the left-hand side of the curve. The Tesla is going so slowly that the driver worries aloud about the semitruck behind him. He’s concerned that the truck might try to pass him on the right though the vehicles
DAVID FRITZ MENTOR, A SIEMENS BUSINESS
are on what is supposed to be a single lane. As the Tesla goes through the curve, it is way off into what NASCAR calls the marbles, small bits of debris that come off tires and vehicles and accumulate near the outside wall of a track. Finally, the Tesla gets around the curve and the driver disengages the autopilot.
In AVs, actuation, sensing, embedded software, and SoCs are highly interdependent
AV functions have been divided into three separate levels: system level, vehicle level, and mobility level.
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8 • 2019
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8/8/19 8:07 AM
