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Ford proposes driver training before unlocking vehicle functions

© A. Krivonosov
A Ford patent outlines training-based access to certain car features. A three-start grace period is only one proposed example.

Three vehicle starts without training, and a feature could be disabled on the fourth. This is an example in a Ford patent application published on October 15, 2026, not technology already deployed in production cars.

Application US20260316768A1, Activation of Functions in Motor Vehicles, distinguishes basic functions such as climate controls, hazard lights and wipers from advanced ones such as adaptive cruise control, automatic high beams and Launch Control.

The owner could decide which features other drivers may use immediately and which require completed training. Manufacturers could protect essential basic functions from being disabled, so the patent does not propose unrestricted blocking of safety systems.

One scenario grants access for three vehicle starts and blocks the feature on the fourth if training remains unfinished. Another allows zero grace starts, requiring instruction before first use.

Training could run on the car's infotainment display while parked, for example with the transmission in Park or the parking brake engaged. It may stop if the driver begins moving.

Remote lessons could be taken on a phone, tablet or computer, potentially using virtual simulations. Completed training would be stored in a driver profile and could transfer to compatible vehicles of the same type.

The proposal also allows temporary or restricted access after partial training. Successful completion could unlock the owner's designated permissions without repeating a test at every start.

Unlike paid feature subscriptions, access here depends on demonstrated knowledge, not a payment. The idea could be useful in shared family vehicles or rental fleets whose drivers have different experience levels.

Ford has not announced the system for production vehicles. Publishing a patent does not establish mandatory driver exams, and implementation dates, supported models and final rules remain unknown.

This English edition was prepared using AI translation under editorial oversight by SpeedMe. The original reporting is by Nikita Novikov

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