Raj Rajkumar, an electrical and computer engineering professor at Carnegie Mellon University, has some insight into this this situation. Other than Tesla itself, Carnegie Mellon is ground zero for autonomous driving development in the world. He tells The Verge that in most road situations, there are vehicles to the front, back, and to the side, but a perpendicular vehicle is much less common. The algorithms using the camera output need to be trained to detect trucks that are perpendicular to the direction of the vehicle.

“Essentially, the same incident repeats after three years,” Rajkumar says. “This seems to indicate that these two problems have still not been addressed.” Machine learning and artificial intelligence have inherent limitations, he explains. If sensors “see” what they have never or seldom seen before, they do not know how to handle those situations. “Tesla is not handling the well-known limitations of AI,” he added.
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