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Understanding how Tesla's FSD handles such tasks illuminates the depth of its capabilities. Unlike traditional systems that rely heavily on pre-programmed maps or GPS signals, Tesla's approach predominantly leverages vision—cameras and computer vision algorithms—to interpret the environment. The system recognizes the stop-line at the drive-thru window, detects the food and card returning through the window, and observes the window's closing motion to determine the appropriate moment to move forward.
This method reflects world-model based intelligence, where the vehicle understands and interprets its surroundings dynamically. It isn't simply following a track or predefined route; it is actively perceiving and making contextual decisions akin to how a human would.