Tesla CEO Elon Musk has alluded to the development of an upcoming “Tap to Park” feature.

Tesla CEO Elon Musk has alluded to the development of an upcoming “Tap to Park” feature.

Tesla CEO Elon Musk has alluded to an upcoming “tap to park” feature for the automaker’s Full Self-Driving (FSD) beta. While it isn’t clear when it’s expected to become available, some have already pointed out how useful such a feature could be.

On Friday, Musk responded to a post on X saying that Tesla is developing a feature in which the car identifies potential parking space options, letting users tap the one they want to use. Upon doing so, the driver will then be able to leave the vehicle before the vehicle parks in the selected space.

The statement came in response to another post claiming that a 360-degree bird’s eye view would be irrelevant in a world of self-driving vehicles, as the driver wouldn’t need to do anything at all for the vehicle to locate and park in a specific spot.



Tesla owners with cars built before the automaker stopped including Ultrasonic Sensors (USS) in its vehicles can also access a similar “Autopark” feature. However, it doesn’t let them select from multiple parking spots, and drivers are expected to remain in the car and ready to regain control unlike the feature Musk describes.

Many of those who have used Autopark have noticed that it still needs some work, and those who have newer cars with Tesla’s camera-based Vision still don’t have Autopark or other advanced features such as Summon and Smart Summon.

You can see an old video from Tesla below showing off how the Autopark feature works in a Model 3.



Tesla did, however, start the rollout of its Tesla Vision Park Assist earlier this year, which approximates the distance between the car and other objects when parking.

The news also comes as Tesla has begun deploying its FSD v12 to employees, as Musk confirmed late last month. The FSD version is expected to include a marked improvement by eliminating several lines of human-written code in place of more reliance on the system’s neural networks as they train from real-world driving video footage.

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