Apple Now Boasts Second Largest Self-Driving Vehicle Fleet In California

Lexus RX 450h
We haven't heard much about Apple's self-driving auto endeavor in recent months, but the company has been working hard behind the scenes. Last December, Apple was in the news when its autonomous vehicle navigation system turned up in a patent filing. That same month, it also showed off its latest self-driving car tech. Apple is big into the autonomous auto game and reports indicate that it now has the second largest autonomous fleet in California.

Apple currently has 55 vehicles cruising the roads (along with 83 trained drivers), GM Cruise has the largest fleet at 104 vehicles and the third largest fleet is Waymo with 51 vehicles. Only a few months back in March, Apple held 45 vehicle permits for testing of autonomous vehicles showing that it has added ten more rides in just a few months. All of these vehicles are reportedly fitted with Apple's self-developed autonomous driving software.

Apple's test vehicles are Lexus RX450h sports utility vehicles fitted with advanced LIDAR equipment and numerous cameras. California does allow testing of fully driverless vehicles on the roads, but as of now, Apple doesn't hold any of those testing permits. All of its autonomous rides roam the streets with a safety driver behind the wheel.

apple building logo

Apple originally had big dreams for its autonomous vehicles with rumors pointing to the development of its own car. In 2016, Apple changed its direction when Bob Mansfield took over the autonomous division. Under his direction, Apple abandoned its car dreams and instead focused on building software for autonomous autos for other automakers.

What Apple has planned for the autonomous driving software when complete is still a mystery. Undoubtedly, Apple would have liked to keep its entire program under wraps, but it can’t due to the need to file for testing permits that are public information.

Apple CEO Tim Cook has spoken on the record about the autonomous software saying, "It's a core technology that we view as very important. We sort of see it as the mother of all AI projects. It's probably one of the most difficult AI projects to actually work on."