Tesla’s Approach to Autonomy: 7x Safer and 7x Cheaper than Waymo
In the race to deploy autonomous vehicles, there have been two schools of thought. One is led by sensor fusion, which means the more sensors and the more types, the better. The other is Tesla’s school of thought — vision.
So far, even Google’s CEO, Sundar Pichai, has described Tesla as the leader in the autonomy sector.
Google CEO on who is the leader in self-driving space: "I think obviously @Tesla is a leader in the space. It looks to me like Tesla and Waymo are the top two." pic.twitter.com/T0hlSICm8V
— Sawyer Merritt (@SawyerMerritt) December 15, 2024
A new analysis from Bloomberg (paywall) offers a similar perspective, focusing on the numbers and real-world safety metrics. Tesla’s strategy isn’t just viable - it is far outpacing its competitors.
A Tale of Crash Rates
The most striking numbers from Bloomberg’s analysis are safety-related. According to their comparison, FSD reports approximately 0.15 crashes per million miles driven. In contrast, Waymo reported approximately 1.16 crashes per million miles.
That means that a Tesla using FSD is seven times less likely to be involved in a crash than a Waymo vehicle, even with its bevy of sensors. This is in line with Tesla’s latest vehicle safety report, which notes that a Tesla using FSD is 10 times less likely to be involved in an accident than a driver in any other vehicle.
When it comes down to it, sensor fusion, while it can be fantastic, it simply provides too much data to process and analyze. While LiDAR, radar and cameras all have their unique advantages, cameras end up being the most versatile. Our roads and world were created around vision and audio, so a LiDAR-only vehicle can’t navigate our roadways since it would be unable to see signs or any other object that lacks depth. For LiDAR to be useful, it needs to be coupled with vision.
Vision works well because it applies to all situations, and it’s a system that continues to improve thanks to advancements in image processing and AI. While measurements with vision still lag behind LiDAR, they’ve reached a point where they’d “good enough,” and the millimeter-level accuracy of LiDAR isn’t needed.
When radar and vision disagree, which one do you believe? Vision has much more precision, so better to double down on vision than do sensor fusion.
— Elon Musk (@elonmusk) April 10, 2021
Vehicle Cost
Besides the difficulty of using sensor fusion, Bloomberg also points out that Tesla’s advantage is in the fundamental cost of the hardware. The Model Y costs just 1/7th of the total cost of a Waymo vehicle.
This enormous cost difference is a direct result of how Tesla and Waymo are approaching autonomy. Waymo’s vehicles are high-end, third-party electric cars, like the now-discontinued Jaguar I-Pace, which are then retrofitted with an expensive, custom-built suite of sensors. This sensor suite includes multiple LIDAR units, radars, and cameras.
Tesla’s ability to scale autonomous driving faster than its rivals gives it an edge in the self-driving race, says Bloomberg Intelligence's Steve Man https://t.co/B1x5Jhx6Lf pic.twitter.com/XYPCblWmXn
— Bloomberg TV (@BloombergTV) June 16, 2025
Tesla, meanwhile, includes all the hardware for autonomy as standard equipment on each of their vehicles, with a relatively inexpensive suite of cameras and its own in-house designed FSD computer. Using affordable hardware means it’s easy to produce and field more vehicles, resulting in more data.
On top of that, building more vehicles at a lower price creates a larger and larger economic difference as time goes on, as Tesla’s Robotaxis become profitable far quicker than Waymo’s.
3 Billion Miles… and Counting
The biggest advantage that Tesla has over any other entrant into the autonomy ring is simply just data. Tesla’s fleet has gathered over 3 billion miles of driving data globally, whereas Waymo’s fleet is just a minuscule 22 million miles.
Putting that into perspective, for every mile driven by a Waymo vehicle, a Tesla has driven over 135. Tesla’s advantage is also the fact that its data is global. It includes vehicles operating in a range of environments, from deserts to the Arctic, from cities to extremely rural areas, and is capable of achieving generalized autonomy.
Waymo’s data is extremely focused on urban and suburban areas and is effectively unusable for generalized vehicle autonomy. A larger, more capable fleet is the key to providing an effective robotaxi service, after all.
Scaling Manufacturing
Finally, Waymo doesn't produce vehicles. Tesla produces Robotaxis from scratch - every vehicle off the line has the ability to run Unsupervised FSD, and eventually join the Robotaxi fleet. Waymo needs to partner with other companies that have a good platform, and they must adapt their technology to that platform.
Waymo’s fleet is expected to be 2,500 vehicles by the end of 2025, while Bloomberg expects Tesla’s functional fleet to hit 35,000 by the same time. That’s not even counting the millions of AI4-powered vehicles that could also join the fleet by late 2026.
Overall, Tesla is a clear winner in the Robotaxi race - and it isn’t just because of one element. They’re winning through data, cost, and scalability, and the gap will only continue to grow.
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