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Tesla Autopilot twists and turns through complex Sin City construction zone on its own
The owner of a Tesla Model S released footage of his electric sedan seamlessly navigating on Autopilot through the sharp and narrow twists and turns of a construction zone.
Model S owner Fred Hassen was traveling on South Las Vegas Boulevard in the “Sin City” while using the vehicle’s Navigate on Autopilot feature as part of the Full-Self Driving suite. The Model S car managed to recognize the confusing lane shifts and road changes and navigate through the cones and safety barrels that were set up by local construction crews. Hassen seemed pleased by his car’s flawless navigation through the make-shift lanes, as can be heard in his video.
The appearance of traffic cones and traffic light indicators on the Model S’ instrument cluster suggests that the vehicle is equipped with Tesla’s latest Hardware 3 and capable of responding to red traffic lights and stop signs, including automatically stopping.
Autopilot progress in clearly marked construction zones is mighty impressive https://t.co/tb1tsuRQaD
— TREV PAGE (@Model3Owners) April 23, 2020
Navigate on Autopilot is one of the most sophisticated driver-assistance features in the automotive industry today. The suite is capable of performing lane changes, navigating through on and off-ramps, and helping drivers make their way through confusing construction zones. The development of Tesla’s software for its self-driving features helps the company work toward a “feature complete” Full Self-Driving suite, which aims to revolutionize the act of driving for every owner in the world.
Tesla’s Artificial Intelligence and Autopilot systems were broken down by Andrej Karpathy, Director of the company’s AI team. Karpathy explained that Tesla’s use of vehicle cameras and artificial intelligence trains its neural network to help cars respond to road conditions safely and accurately. Tesla’s fleet of 1,000,000 vehicles uses “raw images to perform semantic segmentation, object detection, and monocular depth estimation,” according to its website. These images are then used as data to improve the safety of Autopilot.
The data compiled by the fleet of Tesla vehicles is critical to Tesla’s teams who determine improvements that need to be made within the company’s self-driving software. Tesla vehicles likely travel through construction zones every day, but the performance of the cars continues to improve through its continuously-learning Neural Network.
In the past, a Tesla hacker known as “green” has showed Tesla Autopilot’s thought process when navigating through construction zones.
and finally a bit of construction zone (this is the only one of the set where AP is actually on), nothing groundbreaking since it was widely reported already long ago, but still interesting to see it "from the inside": pic.twitter.com/TmGkqhGPQz
— green (@greentheonly) November 7, 2019
The technology seems to recognize cones as the guidance point for the lane, forgetting about painted “on-road” lines when construction zones are concerned. The car understands that the standard path of travel is obsolete because of construction. Autopilot instead uses the cones lined up on both sides of the lane as the new guidance markers for travel. This video is from a previous version of firmware, so the program has improved since then as more data has entered the Neural Network.
Tesla initial plans were to release the “feature complete” FSD suite by the end of 2019, but the program was not ready for a full release. After the company release Stop Sign and Traffic Light recognition in mid-April, all that is left for Tesla to unveil is city driving. As the cars seem to be navigating through tricky construction zones with relative ease, city street driving could roll out soon.
Elon Musk
Tesla confirmed HW3 can’t do Unsupervised FSD but there’s more to the story
Tesla confirmed HW3 vehicles cannot run unsupervised FSD, replacing its free upgrade promise with a discounted trade-in.
Tesla has officially confirmed that early vehicles with its Autopilot Hardware 3 (HW3) will not be capable of unsupervised Full Self-Driving, while extending a path forward for legacy owners through a discounted trade-in program. The announcement came by way of Elon Musk in today’s Tesla Q1 2026 earnings call.
🚨 Our LIVE updates on the Tesla Earnings Call will take place here in a thread 🧵
Follow along below: pic.twitter.com/hzJeBitzJU
— TESLARATI (@Teslarati) April 22, 2026
The history here matters. HW3 launched in April 2019, and Tesla sold Full Self-Driving packages to owners on the understanding that the hardware was sufficient for full autonomy. Some owners paid between $8,000 and $15,000 for FSD during that period. For years, as FSD’s AI models grew more demanding, HW3 vehicles fell progressively further behind, eventually landing on FSD v12.6 in January 2025 while AI4 vehicles moved to v13 and then v14. When Musk acknowledged in January 2025 that HW3 simply could not reach unsupervised operation, and alluded to a difficult hardware retrofit.
The near-term offering is more concrete. Tesla’s head of Autopilot Ashok Elluswamy confirmed on today’s call that a V14-lite will be coming to HW3 vehicles in late June, bringing all the V14 features currently running on AI4 hardware. That is a meaningful software update for owners who have been frozen at v12.6 for over a year, and it represents genuine effort to keep older hardware relevant. Unsupervised FSD for vehicles is now targeted for Q4 2026 at the earliest, with Musk describing it as a gradual, geography-limited rollout.
For HW3 owners, the over-the-air V14-lite update is welcomed, and the discounted trade-in path at least acknowledges an old obligation. What happens next with the trade-in pricing will define how this chapter ultimately gets written. If Tesla prices the hardware path fairly, acknowledges what early adopters are owed, and delivers V14-lite on the June timeline it committed to today, it has a real opportunity to convert one of the longest-running sore subjects among early adopters into a loyalty story.
Elon Musk
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
Tesla’s Optimus factory in Texas targets 10 million robots yearly, with 5.2 million square feet under construction.
Tesla’s Q1 2026 Update Letter, released today, confirms that first generation Optimus production lines are now well underway at its Fremont, California factory, with a pilot line targeting one million robots per year to start. Of bigger note is a shared aerial image of a large piece of land adjacent to Gigafactory Texas, that Tesla has prominently labeled “Optimus factory site preparation.”
Permit documents show Tesla is seeking to add over 5.2 million square feet of new building space to the Giga Texas North Campus by the end of 2026, at an estimated construction investment of $5 billion to $10 billion. The longer term production target for that facility is 10 million Optimus units per year. Giga Texas already sits on 2,500 acres with over 10 million square feet of existing factory floor, and the North Campus expansion is being built to support multiple projects, including the dedicated Optimus factory, the Terafab chip fabrication facility (a joint Tesla/SpaceX/xAI venture), a Cybercab test track, road infrastructure, and supporting facilities.
Credit: TESLA
Texas makes strategic sense beyond the existing infrastructure. The state’s tax structure, lower labor costs relative to California, and the proximity to Tesla’s AI training cluster Cortex 1 and 2, both located at Giga Texas and now totaling over 230,000 H100 equivalent GPUs, means the Optimus software stack and the factory producing the hardware will share the same campus. Tesla’s Q1 report also confirmed completion of the AI5 chip tape out in April, the inference processor designed specifically to power Optimus units in the field.
As Teslarati reported, the Texas facility is intended to house Optimus V4 production at full scale. Musk told the World Economic Forum in January that Tesla plans to sell Optimus to the public by end of 2027 at a price between $20,000 and $30,000, stating, “I think everyone on earth is going to have one and want one.” He has previously pegged long term demand for general purpose humanoid robots at over 20 billion units globally, citing both consumer and industrial use cases.
Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.
The earnings results come after Tesla reported a miss on vehicle deliveries for the first quarter, delivering 358,023 vehicles and building 408,386 cars during the three-month span.
As Tesla transitions more toward AI and sees itself as less of a car company, expectations for deliveries will begin to become less of a central point in the consensus of how the quarter is perceived.
Nevertheless, Tesla is leaning on its strong foundation as a car company to carry forward its AI ambitions. The first quarter is a good ground layer for the rest of the year.
Tesla Q1 2026 Earnings Results
Tesla’s Earnings Results are as follows:
- Non-GAAP EPS –Â $0.41 Reported vs. $0.36 Expected
- Revenues –Â $22.387 billion vs. $22.35 billion Expected
- Free Cash Flow –Â $1.444 billion
- Profit –Â $4.72 billion
Tesla beat analyst expectations, so it will be interesting to see how the stock responds. IN the past, we’ve seen Tesla beat analyst expectations considerably, followed by a sharp drop in stock price.
On the same token, we’ve seen Tesla miss and the stock price go up the following trading session.
Tesla will hold its Q1 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.
You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.
Q1 2026 Earnings Call at 4:30pm CT https://t.co/pkYIaGJ32y
— Tesla (@Tesla) April 22, 2026
Tesla confirmed HW3 can’t do Unsupervised FSD but there’s more to the story
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
