Musk's dream of self-driving Tesla fleets looks as distant as ever

Cracks are appearing in Elon Musk’s plan to maintain sky-high valuations for Tesla by pivoting to full autonomy. 

Musk has long promised his company would be able to update the majority of Teslas on the road to drive unsupervised, starting with robotaxi rides at the company’s home city in Austin, Texas, from June.

Musk confirmed the timeline on the company’s first-quarter earnings call on Tuesday 22 April and promised a quick roll-out of the technology for private cars. “I bet there will be millions of Teslas operating fully autonomously in the second half of next year,” Musk said. Drivers would be able to sleep in their car while it drives to its destination “by the end of this year,” he promised.

Musk’s bold statements and trademark confidence were deployed against possible fallout from a poor quarter in which automotive revenue sank 21% and the only factor stopping the company from dropping into the red were increased emissions credits paid to Tesla by other car makers.

However, questions from investors teased out more information from Musk and his lieutenants, revealing that the company’s plan to transform the Tesla fleet with a mere push of a software update is likely to remain a pipe dream.

For instance, Musk spoke about standard cars needing a “localised set of parameters for different regions and localities” to deal with, for example, snowy weather in the north-east of the US. 

In other words, far from being point-to-point self-driving, any upgrade would be to a very limited level-three autonomy, with cars taking control within restricted operational design domains (ODDs). This is a well-understood condition by which Mercedes and BMW released their level-three autonomous features for the S-Class and 7 Series respectively, which are limited for use on highways in Germany and California and then only at restricted speeds. 

As with BMW and Mercedes, a full geographical roll-out isn’t in the gift of Tesla but of law makers in whichever jurisdiction the company is targeting.

Tesla’s long-held dream is that it can activate full self-driving across almost its entire fleet, provided the chip is new enough to handle the extra computing load.

By relying on AI machine-learning and just cameras as sensors, Tesla can build cars relatively cheaply while still retaining the ability to one day transform them with a simple software push, if it can train its self-driving AI to deal with every eventuality.