Tesla FSD Milestone: FSD Now Drives 1 Million Miles Per Day

April 6, 2023

By Kevin Armstrong

Musk says Tesla vehicles are now driving 1 million miles per day using FSD Beta

Not a Tesla App

Tesla's Full Self-Driving (FSD) technology has reached an impressive milestone, as revealed by CEO Elon Musk in a recent tweet. Equipped with the latest FSD update, Tesla vehicles are now actively driving approximately 1 million miles per day across the fleet. This achievement signals significant progress in Tesla's quest to perfect autonomous driving as the company continues to refine its technology and expand its capabilities.

Rapid Improvements in FSD Technology

According to Musk's tweet, Tesla's team has been "closing the loop on interventions very rapidly," meaning that the FSD software is learning from user feedback and real-world driving scenarios at an accelerated pace. This has led to fewer necessary interventions by drivers, making the technology more reliable and safer for everyday use. With Tesla's FSD software now actively driving 1 million miles per day, it becomes evident that these improvements are being utilized not just by FSD Beta testers but across the entire Tesla fleet.

As we recently reported, Tesla is using information from the fleet to improve maps, navigation and FSD.

Given the impressive daily mileage figure, we can estimate the average miles driven per vehicle by dividing the total miles by the number of Tesla vehicles on the road. While it's difficult to provide an exact number, it's clear that the FSD technology is experiencing widespread usage, contributing to the rapid improvement in performance.

Simulated Training for Potential Serious Accidents

As Musk's tweet suggests, Tesla increasingly relies on simulated training to enhance the FSD software, especially in situations where potential serious accidents may occur. The reason behind this reliance on simulations is the scarcity of real-world data for such incidents, owing to the relatively low number of accidents within the Tesla fleet. By running these scenarios in a simulated environment, Tesla can train its FSD system to handle dangerous situations more effectively without putting actual drivers and passengers at risk.

As Tesla continues to refine its Full Self-Driving technology, the impressive milestone of 1 million miles driven per day across the fleet marks a significant step forward in the company's pursuit of perfecting autonomous driving. With rapid improvements in FSD performance and an increasing reliance on simulated training, Tesla's dedication to safety and innovation shines through, solidifying its position as a leader in the EV and autonomous vehicle industry.

Tesla’s Robotaxi Easter Egg: Surprise Tip

June 25, 2025

By Karan Singh

BLKMDL3

Tesla has always embraced whimsy in its software, packing it with playful Easter eggs and surprises. From transforming the on-screen car into James Bond’s submarine to the ever-entertaining Emissions Testing Mode and the fan-favorite Rainbow Road, these hidden features have become a signature part of Tesla’s software.

Of course, launching a new product like Robotaxi wouldn’t be complete without a fun little easter egg of its own. The end-of-ride screen in the Robotaxi app presents a familiar option “Leave a tip.”

For anyone pleased with their Robotaxi ride, they may be tempted to leave a tip. However, tapping the button presents our favorite hedgehog instead of a payment screen.

The app displays a message, alongside the familiar Tesla hedgehog, that simply states “Just kidding.”

While it's a fun prank, it’s also a nod to what Tesla really wants to do. They want to reinforce the economic advantage of an autonomous Robotaxi Network. Without a driver, there is simply no need to tip. The gesture is playful, but it’s a reminder of what Tesla’s real aim is here.

Had to been done lol https://t.co/SnZ3afXXzB
— Elon Musk (@elonmusk) June 22, 2025

Even Elon is in on the joke. It is a small detail, but it’s all about those small details with Tesla.

First Recorded Tesla Robotaxi Intervention: UPS Truck Encounter [VIDEO]

June 25, 2025

By Karan Singh

@BLKMDL3 on X

Over the last few days, we’ve seen some exceptionally smooth performance from the latest version of FSD on Tesla’s Robotaxi Network pilot. However, the entire purpose of an early access program with Safety Monitors is to identify and learn from edge cases.

This week, the public saw the first recorded instance of a Safety Monitor intervention, providing a first look at how they’re expected to stop the vehicle.

The event involved a complex, low-speed interaction with a reversing UPS truck. The Safety Monitor intervened to stop the Robotaxi immediately, potentially avoiding a collision with the delivery truck. Let’s break down this textbook case of real-world unpredictability.

The Intervention [VIDEO]

In a video from a ride in Austin, a Robotaxi is preparing to pull over to its destination on the right side of the road, with its turn signal active. Ahead, a UPS truck comes to a stop. As the Model Y begins turning into the spot, the UPS truck, seemingly without signaling, starts to reverse. At this point, the Safety Monitor stepped in and pressed the In Lane Stop button on the main display, bringing the Robotaxi to an immediate halt.

This is precisely why Tesla has employed Safety Monitors in this initial pilot. They are there to proactively manage ambiguous situations where the intentions of other drivers are unclear. The system worked as designed, but it raises a key question: What would FSD have done on its own? It’s not clear whether the vehicle saw the truck backing up, or what it would do when it finally detected it. It’s also unclear whether the UPS driver recognized that the Robotaxi was pulling into the same spot at the exact same time.

It’s possible this wouldn’t result in a collision at all, but the Safety Monitor did the right thing by stepping in to prevent a potential collision, even one at low speed. Any collision just a few days after the Robotaxi Network launch could result in complications for Tesla.

Who Would Be At Fault?

This scenario is a classic edge case. It involves unclear right-of-way and unpredictable human behavior. Even for human drivers, the right-of-way here is complicated. While a reversing vehicle often bears responsibility, a forward-moving vehicle must also take precautions to avoid a collision. This legal and practical gray area is what makes these scenarios so challenging for AI to navigate.

Would the Robotaxi have continued, assuming the reversing truck would stop?

Or would it have identified the potential conflict and used its own ability to stop and reverse?

Without the intervention, it’s impossible to say for sure. However, crucial context comes from a different clip involving, surprisingly, another UPS delivery truck.

A Tale of Two Trucks

In a separate video posted on X, another Robotaxi encounters a remarkably similar situation. In that instance, as another UPS delivery truck obstructs the path forward, the Robotaxi comes to a stop to let its two passengers out just a few feet from their destination.

Once they depart, the Robotaxi successfully reverses and performs a three-point turn to extricate itself from a tight spot. That was all done without human intervention, by correctly identifying the situation.

This second clip is vital because it proves that the Robotaxi's FSD build has the underlying logic and capability to handle these scenarios. It can, and does, use reverse to safely navigate complex situations.

RUN THE CLIP!

UPS Truck vs Tesla Robotaxi https://t.co/GLc86BS5bc pic.twitter.com/O2c8c2KRB2
— Bradford Ferguson (@bradsferguson) June 25, 2025

A Valuable Data Point

Far from being a failure, this first intervention should be seen as a success for Tesla’s safety methodology. It shows the safety system is working, allowing monitors to mitigate ambiguous events proactively.

More importantly, this incident provides Tesla’s FSD team with an invaluable real-world data point.

By comparing the intervened ride with the successful autonomous one, Tesla’s engineers can fine-tune FSD’s decision-making, which will likely have a positive impact on its edge case handling in the near future.

This is the purpose of a public pilot — to find the final edge cases and build a more robust system, one unpredictable reversing truck at a time.