Tesla recently published its Q4 2019 Vehicle Safety Report and it puts on the spotlight that accidents involving Teslas are still rarer compared to other vehicles on the road.
Tesla’s Vehicle Safety Report for Q4 2019 revealed that a Tesla on Autopilot was involved in one accident for every 3.07 million miles driven. For those without Autopilot but use the active safety features of the vehicle, there was one accident per 2.10 million miles driven. Tesla owners who do not use Autopilot and other active safety features were involved in one accident for every 1.64 million miles driven. Overall, these numbers are far better than what’s been recorded by the National Highway Traffic Safety Administration (NHTSA) which indicates there being one automobile crash in the United States every 479,000 miles.
The Q4 accidents involving Teslas are a bit higher compared with the previous quarter when it registered one accident for every 4.34 million miles for those using Autopilot. Those who do not have the Autopilot engaged but use active safety features were involved in one accident per 2.19 million miles driven. Those who do not use Autopilot and active safety features of Teslas were involved in one road mishap per 1.41 million miles.
The apparent decline in the safety statistics can be attributed to the time of the year when the roads are busier because of several holidays such as Thanksgiving and Christmas Day in the United States. Weather can also be a factor that may have worsened driving conditions. However, one still cannot deny that the numbers are impressive as driving with Autopilot engaged is still more than six times safer than the average, and driving without Autopilot or active safety features is still three to four times safer compared to the average.
“Accident rates among all vehicles on the road can vary from quarter to quarter and can be affected by seasonality, like reduced daylight and inclement weather conditions,” Tesla’s microsite on Vehicle Safety Report reads. “Model S, Model X and Model 3 have achieved the lowest probability of injury of any vehicle ever tested by the U.S. government’s New Car Assessment Program.”
In terms of vehicle fire data, the electric car manufacturer summarized that between 2012 and 2019, there’s only one Tesla vehicle fire for every 175 million miles traveled. In contrast, there’s one vehicle fire reported by the U.S. Department of Transportation and the National Fire Protection Association (NFPA) for every 19 million miles traveled. This is an improvement compared to the 2012-2018 Vehicle Fire Date where Tesla registered one vehicle fire for every 170 miles traveled.
Tesla vehicles are among the safest cars in the world today. For example, Tesla Model 3 earned an overall rating of 5 stars in the NHTSA 2019 safety rating. The mass-produced electric sedan, together with its Model X sibling, also took top honors in Euro NCAP’s Best in Class Cars 2019 List.
With the improvement of the Autopilot and the Full Self-Driving capabilities of Teslas, we can only expect these Tesla safety statistics to improve and this will eventually lead to safer roads for other vehicles and for pedestrians as well.
You can read Tesla’s Q4 2019 Vehicle Safety Report below:
Accident Data
In the 4th quarter, we registered one accident for every 3.07 million miles driven in which drivers had Autopilot engaged. For those driving without Autopilot but with our active safety features, we registered one accident for every 2.10 million miles driven. For those driving without Autopilot and without our active safety features, we registered one accident for every 1.64 million miles driven. By comparison, NHTSA’s most recent data shows that in the United States there is an automobile crash every 479,000 miles.
Vehicle Fire Data
Tesla Hardware 3 owners are set to get a new Full Self-Driving version this month as the company plans to release what it is referring to as v14 Lite.
The rollout is not yet confirmed for June, but Tesla executives have stated on several occasions that this more refined FSD iteration will work with their cars and increase its capabilities.
This comes after Tesla admitted during its last Earnings Call that these Hardware 3 vehicles would not be able to achieve Full Self-Driving, something that they did not know when they bought these cars. We regularly receive messages from Hardware 3 owners asking when v14 Lite will come out, what they should expect, and whether it is worth it to upgrade the self-driving computer or buy a new car altogether.
Following future rollout of FSD V14 Lite for HW3 vehicles in the US, we plan on expanding V14 Lite to additional international markets.
This update ensures that HW3 vehicle owners will continue to benefit from ongoing software updates.
Since international rollout is subject to…
— Tesla (@Tesla) April 29, 2026
It is hard not to feel for them; Tesla CEO Elon Musk said at the company’s 2019 Autonomy Day that all vehicles produced at the time, including Hardware 3 cars, had “all the hardware necessary, compute and otherwise, for Full Self-Driving.”
Musk also said in March of that year that, “Anyone who purchased Full Self-Driving will get FSD computer upgrade for free.”
Anyone who purchased full self-driving will get FSD computer upgrade for free. This is the only change between Autopilot HW2.5 & HW3. Going forward “HW3” will just be called FSD Computer, which is accurate. No change to vehicle sensors or wire harness needed. This is v important. https://t.co/lICMpT7xnX
— Elon Musk (@elonmusk) March 29, 2019
However, during the Q1 2026 Earnings Call, Musk admitted that Hardware 3 vehicles would not be capable of FSD, as “It has only 1/8th the memory bandwidth of Hardware 4, and memory bandwidth is one of the key elements needed for unsupervised FSD.”
Tesla has made some effort to remedy these Hardware 3 owners by offering:
- Discounted trade-ins toward AI4 cars
- Hardware retrofits, which would replace the self-driving computer and upgrade all cameras
- Full Self-Driving v14 Lite
The issue is that many of these owners were led to believe their cars would be capable of unsupervised self-driving. Now, they’re left scrambling for options, and while there are several, they will all require more money out of their pockets.
Expectations for Tesla v14 Lite for Hardware 3 Owners
The big differences between the AI4 v14 and v14 Lite for Hardware 3 owners will stem primarily from hardware constraints. Tesla developed v14 Lite with an optimized frame of mind; the v14 neural nets are toned down to run on an HW3 computer.
Tesla v14 will use the same behavior, but its limits will be hardware-related, especially given that the cameras on HW3 vehicles are lower-resolution.
Tesla reveals its plans for Hardware 3 owners who are eager for updates
This will result in potentially more edge cases due to the lower quality perception and less long-range detection, but reaction time and overall confidence should be more refined.
There should also be a handful of additional features that are available on AI4 cars, such as:
- Starting Full Self-Driving from Park
- Auto Shift
- Streaks
- Speed Profiles
- Improved Dynamics, like Pulling Over for Emergency Vehicles
Tesla plans to release v14 Lite this month, but we are all familiar with how the company can be with timelines. Additionally, if v14 Lite has not proven to be ready for a wide release, Tesla will slam the brakes on the rollout.
We would anticipate that Tesla is testing v14 Lite internally, and likely has been for several months.
Elon Musk
SpaceXAI just launched into your kitchen with their new app
SpaceXAI just powered its first consumer app and it predicts what you want to buy.
SpaceXAI just made its first move into consumer AI, and it involves your grocery cart. On June 3, 2026, Gopuff and SpaceXAI announced the launch of Go, a Grok-powered shopping assistant built directly into the Gopuff app that predicts what you need before you even start searching for it.
Gopuff is an instant delivery platform that operates more than 400 micro-fulfillment centers across the U.S., delivering everyday essentials, snacks, drinks, and household items in as little as 15 minutes. It is not a restaurant delivery app or a marketplace. It owns its inventory, controls its warehouses, and handles its own logistics, which means it has built one of the most detailed consumer behavior datasets in retail over its 13-year history.
Go combines SpaceXAI’s advanced reasoning, voice, and image generation models with Gopuff’s dataset of hundreds of millions of orders and real-time cultural signals from X to prepare a suggested cart the moment a customer opens the app. It learns each shopper’s habits and automatically builds a personalized cart based on time of day, location, order history, and real-time indicators. Returning customers can check out with a single tap.
Rather than searching for specific items, users can describe a situation like a game-day party or the desire for a healthy breakfast and Go will assemble a cart automatically. It can also predict when shoppers are running low on items like coffee or paper towels and have them packed and delivered in under 15 minutes. Grok voice integration lets users talk to the app in plain conversational language and check out completely hands-free.
Gopuff co-founder and co-CEO Yakir Gola said: “Today, we believe the greatest friction left in commerce is not delivery or instantaneous access to the essentials customers need. It’s the moment before: the thinking, the deciding, the remembering. We’re combining Gopuff’s demand intelligence with xAI’s frontier reasoning to create an everyday shopping experience that feels like a true extension of you.”
Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO
The timing carries context beyond the product launch. SpaceXAI was formed after SpaceX completed an all-stock merger with Elon Musk’s xAI earlier this year, folding one of the most advanced AI labs in the world into the same corporate structure as the company preparing what could be the largest IPO in history. SpaceXAI is dipping into consumer-focused AI just as it prepares for its public debut, and while Musk has openly discussed building an everything app, this launch uses Grok to power another company’s product rather than launching a standalone consumer platform. Every consumer-facing deployment of Grok ahead of the IPO roadshow adds tangible evidence that SpaceXAI is not just an infrastructure play but a direct competitor in the AI application layer where OpenAI and Google are already fighting for dominance.
Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.
This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.
The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.
Tesla supplements Holiday Update by sneaking in new Full Self-Driving version
Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.
Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:
Supercharger update now shows type of Tesla at charger as well.
Pretty cool. pic.twitter.com/J3NRSIgM0m
— DennisCW | wen my L (@DennisCW_) June 2, 2026
This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.
Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.
Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.
Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.
In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.
As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.
With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.
Tesla Hardware 3 owners could be made whole this month
SpaceXAI just launched into your kitchen with their new app
