Google’s driverless ride-hailing company Waymo has revealed the latest in a string of AI research-related announcements, this time sharing results from a first-of-its-kind study on collisions with vulnerable road users.
Waymo last week announced EMMA, its end-to-end, multimodal research model for autonomous driving, though it isn’t being used commercially at this point. The company also went on to detail its current approach to AI in a separate press release, noting its continued research into real-world models and AI training, a concept that may sound familiar to those who have followed Tesla’s Full Self-Driving (FSD) development.
On Monday, however, Waymo shared results from a study on Vulnerable Road Users (VRUs), in which the company reconstructed hundreds of collisions involving VRUs like pedestrians, cyclists, and motorcyclists. Waymo says that the research, as conducted in a partnership with Nexar, is the largest dataset of its kind in the U.S., providing key insights into real-world crash scenarios.
The companies analyzed dash camera footage of 335 collisions involving VRUs across six U.S. cities, leveraging over 500 million miles of driving data from Nexar for the research. The partnership also worked with Waymo research partner VUFO, which contributed to the below models on collision injury risk.

Credit: Waymo

Credit: Waymo
According to the National Highway Traffic Safety Administration (NHTSA), there were an estimated 7,522 pedestrians and 1,105 cyclists who lost their lives in traffic crashes in 2022, though Waymo says VRU collision data remains scarce. The company explains this by noting that several VRU-related incidents don’t get reported to authorities or insurance firms, while the U.S. and other major accident databases lack data on these particular incidents.
“We’re excited to partner with Waymo on this cutting-edge research,” said Henrik Liers, Managing Director of Waymo research partner VUFO. “Our common work addresses critical limitations in existing models and provides a more precise, interdisciplinary approach to assessing injury risk for vulnerable road users. This is a significant contribution towards improving road safety.”
Tesla’s Full Self-Driving and end-to-end learning models
The recent developments from Waymo come as General Motors’s (GM’s) Cruise, Amazon’s Zoox, and Tesla’s Supervised Full Self-Driving (FSD) aim to offer similar robotaxi services. While Tesla doesn’t currently operate a paid ride-hailing service as Waymo does, it unveiled the two-seat, steering wheel-free Cybercab robotaxi last month.
Interestingly, Tesla’s FSD system has been touted by some as a more scalable solution, in no small part due to its end-to-end system that trains on millions of clips of real-time driving footage. Another factor is that FSD is available to any Tesla owner who purchases the software, meaning that its neural network stands to have a much wider potential research base than systems like Waymo—at least until services scale up substantially.
Tesla’s Cybercab isn’t expected to go into production until 2026, though FSD Supervised will certainly collect a substantial amount of data in the meantime. As of Tesla’s Q3 earnings call, the company has over 2 billion cumulative miles of data from FSD Supervised users, after it surpassed a milestone of 1.3 billion miles in April.
Tesla FSD V13 to implement features required for unsupervised driving: exec
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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.
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.
Investor's Corner
Tesla (TSLA) Q1 2026 earnings results: beat on EPS and revenues
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 – $0.41 Reported vs. $0.36 Expected
- Revenues – $22.387 billion vs. $22.35 billion Expected
- Free Cash Flow – $1.444 billion
- Profit – $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
