Tesla detecting distance without ultrasonic sensors
salvagEV's/YouTube
Tesla owner and EV mechanic Occupy Mars shared a video of their salvaged 2018 Tesla Model 3 detecting distances without its ultrasonic sensors (USS).
Occupy Mars shared a 10.5-minute video explaining how they discovered this anomaly. Even though the vehicle was running version 2022.28.2, which was released in September 2022, the vehicle managed to measure distances without the use of USS.
Occupy Mars moved the vehicle out of their garage without the front bumper and confirmed that all ultrasonic sensors were disconnected. However, they noticed that their Model 3 was accurately detecting a vehicle next to it and displaying the appropriate distances on the screen. This appears to confirm that Tesla is testing Tesla Vision to detect nearby objects and display distances, but only on vehicles with USS.
Confirming Camera Detection
Interestingly, Occupy Mars' vehicle only detected the distances while in reverse, although a lot of the car is taken apart, so this could have been due to early software or hardware issues. When pulling up closer to the garage, Occupy Mars noticed the Model 3 was not showing the distance between the car and the garage. Instead, it was detecting objects at the corners of the vehicle. This would make sense given the blindspot in front of the vehicle where cameras can not see.
To confirm that the vehicle was using its cameras to determine distances, Occupy Mars covered the front-facing and B-pillar cameras with tape. Once the vehicle's cameras were covered, the car immediately stopped displaying the arcs and distances from nearby objects.
Occupy Mars went a step further to rule out radar use and physically unplugged the vehicle's radar and with the cameras uncovered, the vehicle continued to detect objects and display distances.
Video Showing USS-like Detection Using Vision
The video below by Occupy Mars shows their vehicle detecting distances without utilizing any ultrasonic sensors or radar.
Running Vision in Shadow Mode
What appears to be happening is that Tesla is actively testing and collecting data from vehicles that are equipped with ultrasonic sensors, and it appears they've been doing so for several months. Previously, the USS were fully responsible for detecting distances for nearby objects, but it appears Tesla is now using an updated version of Tesla Vision in shadow mode. This lets Tesla run code in the background to assess its accuracy before having the vehicle or driver rely on it. Tesla then uses the vision-detected distances and compares those values to the output of the vehicle's ultrasonic sensors, letting them assess the new system's accuracy before releasing it publicly.
The Removal of Ultrasonic Sensors
On October 4th, 2022, Tesla announced that they were removing ultrasonic sensors from their vehicles and beginning the transition into their own proprietary “Tesla Vision.” According to Tesla’s announcement, Model 3 and Model Y vehicles built in October 2022 and beyond no longer included the USS. Later, Tesla removed USS from the Model S and Model X as well.
This came as a bit of a shock to drivers and automotive experts, namely the team from Munro Live. The USS are standard in modern vehicles. They’re used to detect distances in tight spaces to enhance the safety of the vehicle. But Tesla believes they can maintain a similar level of safety and accuracy without the USS, despite some outcry from the Tesla community and experts.
Savings Due to the Removal of Ultrasonic Sensors
Tesla is saving an estimated $114 per vehicle by removing the USS, equating to roughly 100 million dollars per year based on Tesla’s volume, per Munro Live. This effort makes sense as Tesla is revamping its Model 3 to cut costs so prospective buyers can take advantage of the new federal tax credit.
Front Blindspot
Will Teslas have a blind spot directly in front of the vehicle?
Munro Live
As pointed out in the Munro Live video, there is a three-foot blindspot in the front of the vehicle. Tesla’s rumored solution for the three-foot blindspot is to have the vehicle remember what it sees when driving toward an object. But if the vehicle is parked for an extended period and something is placed in front of it, how will the vehicle know where it’s placed or if it has moved?
Tesla could continue processing camera data while parked as they do in Sentry Mode, but this would cause significant battery usage over time.
Tesla may also just leave out the ability to detect objects in front of the vehicle when the vehicle is first started.
Upcoming Update
More recently Tesla owner and hacker GreenTheOnly found code of Tesla testing vision-based USS-type detection in update 2022.40, so it's clear that Tesla plans to address the lack of USS, but it appears the fix is taking longer than expected. Although nothing has been officially communicated by Tesla, we could be close to receiving the long-awaited update that restores USS-type detection.
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With Tesla’s first major expansion of the Robotaxi Geofence now complete and operational, they’ve been hard at work with validation in new locations - and some are quite the drive from the current Austin Geofence.
Validation fleet vehicles have been spotted operating in a wider perimeter around the city, from rural roads in the west end to the more complex area closer to the airport. Tesla mentioned during their earnings call that the Robotaxi has already completed 7,000 miles in Austin, and it will expand its area of operation to roughly 10 times what it is now. This lines up with the validation vehicles we’ve been tracking around Austin.
Based on the spread of the new sightings, the potential next geofence could cover a staggering 450 square miles - a tenfold increase from the current service area of roughly 42 square miles. You can check this out in our map below with the sightings we’re tracking.
If Tesla decides to expand into these new areas, it would represent a tenfold increase over their current geofence, matching Tesla’s statement. The new area would cover approximately 10% of the 4,500-square-mile Austin metropolitan area. If Tesla can offer Robotaxi services in that entire area, it would prove they can tackle just about any city in the United States.
From Urban Core to Rural Roads
The locations of the validation vehicles show a clear intent to move beyond the initial urban and suburban core and prepare the Robotaxi service for a much wider range of uses.
In the west, validation fleet vehicles have been spotted as far as Marble Falls - a much more rural environment that features different road types, higher speed limits, and potentially different challenges.
In the south, Tesla has been expanding towards Kyle, which is part of the growing Austin-San Antonio suburban corridor spanning Highway 35. San Antonio is only 80 miles (roughly a 90-minute drive) away, and could easily become part of the existing Robotaxi area if Tesla obtains regulatory approval there.
In the East, we haven’t spotted any new validation vehicles. This is likely because Tesla’s validation vehicles originate from Giga Texas, which is located East of Austin. We won’t really know if Tesla is expanding in this direction until they start pushing past Giga Texas and toward Houston.
Finally, there have been some validation vehicles spotted just North of the new expanded boundaries, meaning that Tesla isn’t done in that direction either. This direction consists of the largest suburban areas of Austin, which have so far not been serviced by any form of autonomous vehicle.
Rapid Scaling
This new, widespread validation effort confirms what we already know. Tesla is pushing for an intensive period of public data gathering and system testing in a new area, right before conducting geofence expansions. The sheer scale of this new validation zone tells us that Tesla isn’t taking this slowly - the next step is going to be a great leap instead, and they essentially confirmed this during this Q&A session on the recent call. The goal is clearly to bring the entire Austin Metropolitan area into the Robotaxi Network.
While the previous expansion showed off just how Tesla can scale the network, this new phase of validation testing is a demonstration of just how fast they can validate and expand their network. The move to validate across rural, suburban, and urban areas simultaneously shows their confidence in these new Robotaxi FSD builds.
Eventually, all these improvements from Robotaxi will make their way to customer FSD builds sometime in Q3 2025, so there is a lot to look forward to.
For years, the progress of Tesla’s FSD has been measured by smoother turns, better lane centering, and more confident unprotected left turns. But as the system matures, a new, more subtle form of intelligence is emerging - one that shifts its attention to the human nuances of navigating roads. A new video posted to X shows the most recent FSD build, V13.2.9, demonstrating this in a remarkable real-world scenario.
Toll Booth Magic
In the video, a Model Y running FSD pulls up to a toll booth and smoothly comes to a stop, allowing the driver to handle payment. The car waits patiently as the driver interacts with the attendant. Then, at the precise moment the toll booth operator finishes the transaction and says “Have a great day”, the vehicle starts moving, proceeding through the booth - all without any input from the driver.
If you notice, there’s no gate here at this toll booth. This interaction all happened naturally with FSD.
While the timing was perfect, the FSD wasn’t listening to the conversation for clues (maybe one day, with Grok?) The reality, as explained by Ashok Elluswamy, Tesla’s VP of AI, is even more impressive.
It can see the transaction happening using the repeater & pillar cameras. Hence FSD proceeds on its own when the transaction is complete 😎
FSD is simply using the cameras on the side of the vehicle to watch the exchange between the driver and attendant. The neural network has been trained on enough data that it can visually recognize the conclusion of a transaction - the exchange of money or a card and the hands pulling away - and understands that this is the trigger to proceed.
The Bigger Picture
This capability is far more significant than just a simple party trick. FSD is gaining the ability to perceive and navigate a world built for humans in the most human-like fashion possible.
If FSD can learn what a completed toll transaction looks like, it’s an example of the countless other complex scenarios it’ll be able to handle in the future. This same visual understanding could be applied to navigating a fast-food drive-thru, interacting with a parking garage attendant, passing through a security checkpoint, or boarding a ferry or vehicle train — all things we thought that would come much later.
These human-focused interactions will eventually become even more useful, as FSD becomes ever more confident in responding to humans on the road, like when a police officer tells a vehicle to go a certain direction, or a construction worker flags you through a site. These are real-world events that happen every day, and it isn’t surprising to see FSD picking up on the subtleties and nuances of human interaction.
This isn’t a pre-programmed feature for a specific toll booth. It is an emergent capability of the end-to-end AI neural nets. By learning from millions of videos across billions of miles, FSD is beginning to build a true contextual understanding of the world. The best part - with a 10x context increase on its way, this understanding will grow rapidly and become far more powerful.
These small, subtle moments of intelligence are the necessary steps to a truly robust autonomous system that can handle the messy, unpredictable nature of human society.
