As impressive as Tesla's system is -- and make no mistake, it is deeply impressive -- navigating the Stanford campus is a hurdle that even graduate school projects are able to clear.
Tesla's new sensor suite upgrades what was a single forward-facing camera to eight cameras giving a 360-degree view around the car. It also updates the 12 ultrasonic sensors, while keeping a single forward-facing radar. Yet independent experts and representatives from competitor firms tell me this system is still insufficient for full level 5 autonomy -- the National Highway Traffic Safety Administration's highest rating -- which requires more (and better) radar, multiple cameras with different apertures at each position and 360-degree laser-sensing capabilities.
What Tesla's upgraded hardware does do is vastly improve the company's ability to pull high-quality data from its vehicles already on the road, giving it an unrivaled ability to comply with new regulatory guidelines requiring granular data about autonomous-drive functions in a variety of conditions.
Whereas its competitors' autonomous-drive programs harvest data from small test fleets and extrapolate from there, Tesla has made every car it sells into an independent experiment of conditions that can only be found on the open road. All this real-world data gives Tesla a unique opportunity to validate its autopilot technology.
If the company had announced Autopilot 2.0 as another step toward an eventual fully autonomous system, this would be an unambiguously good (if not earth-shattering) development.
Unfortunately, that's not what Tesla did. Instead, in Wednesday's launch events, it called its new hardware suite "full self-driving hardware." It said the technology would demonstrate the system's ability to drive cross-country without any human intervention. Tesla even hinted that a feature will allow its cars to be rented out as autonomous taxis when not in use by their owners.