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Tesla’s no-side-mirror approach becomes feasible as NHTSA ponders camera-based systems
When Tesla unveiled the next-generation Roadster and the Cybertruck to the world, the two vehicles immediately shocked the automotive industry. The Roadster stunned because of its insane specs, and the Cybertruck shocked because of its unorthodox design that is unlike any other pickup truck on the market. However, the two vehicles also share something very unique: they both lack side mirrors.
Federal Motor Vehicle Safety Standard No. 111, titled “Rear Visibility,” requires all vehicles to “be equipped with rearview mirrors to provide drivers with a view of objects that are to their side or their side and rear.” However, the NHTSA recently hinted that “light vehicles and heavy trucks” may eventually be equipped with camera systems instead of traditional side mirrors.
An edition of the United States government’s Federal Register from late 2019 shows the National Highway Transportation Safety Administration sought more information on the possibility of vehicles utilizing a “Camera Monitor System,” or CMS. The removal of mirrors instead of camera systems would eliminate the need for traditional side mirrors and possibly rearview mirrors, too.
Tesla’s absence of side mirrors started back in 2013 with the unveiling of the Model X. After wrestling with the idea of a side-mirrorless SUV to increase aerodynamic performance, CEO Elon Musk stated that manufacturers were required to install side mirrors on vehicles. A side mirror-less design actually benefits electric cars like Teslas, since side mirrors increase drag, reducing range. This was done by Audi with the e-tron, with the vehicle being offered with a side mirror-less trim that is slightly more efficient.
The Cybertruck’s side mirrors were absent during its unveiling event in November 2019. Instead of regular mirrors, Tesla had equipped the vehicle with Autopilot cameras that are in the truck’s front fender. Many enthusiasts of the electric carmaker speculated that this was a design that wouldn’t enter production as regulations still existed that required side mirrors.
To determine the effectiveness of camera systems instead of traditional mirrors, the NHTSA conducted its research and testing. The organization also examined testing performed by other parties. The CMS noted that during a trial period from 2006 to 2011, NHTSA research showed that several safety concerns arose from the use of cameras instead of mirrors. These stemmed from glares when sunlight touched the cameras. However, the German Federal Highway Research Institute published a separate study that showed the CMS meets “specific quality criteria” and can provide “sufficient” rear visibility for drivers.
So the question is: What has changed in the nine years since the study concluded? For one, cameras have gotten significantly better. What was once a quality piece of photography equipment can be found on the back of an iPhone. High-resolution pictures and videos are not uncommon, and it is not rare for even extremely affordable cameras to provide better quality images than what was available in 2011.
To determine an accurate and fair assessment of the CMS, a new study should be performed using the 2020 technology. The use of rearview backup cameras is a standard feature on most vehicles today. While such systems are used mostly when backing into a parking spot, it is still relevant, and it shows that the widely adopted technology can be used in an effective and safe manner. This feature could be expanded on, and mirrors could be removed from vehicles if the proper research was performed and quality cameras were placed on a vehicle’s exterior.
Tesla has hinted at mirrorless driving in the past, and the door is open now more than ever. It seems this system could be integrated into performance vehicles like the Roadster, or pickups like the Cybertruck in the future. The designs of these two all-electric vehicles have hinted towards a future that does not include traditional side mirrors, which could change the way other carmakers design vehicles as a whole. Tesla’s minimalistic interior and large centrally-located dash screen has been adopted by many other carmakers, showing the electric car company influences other automakers in the industry. A side-mirror-less theme may be the next big trend that Tesla starts.
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
