News
SpaceX’s orbital Starship prototype gets frosty during first successful ‘cryoproof’
For the first time, SpaceX has put the first orbital-class Starship – a prototype known as Ship 20 (S20) – through a routine cryogenic proof test, filling the rocket with several hundred tons of liquid nitrogen to simulate its explosive propellant.
While it’s impossible to jump to conclusions before members of the public can return to the pad to take photos or CEO Elon Musk takes to Twitter to discuss the results, Ship 20’s first ‘cryoproof’ appears to have been largely successful [Edit: Musk has confirmed that the test went well]. Relative to the almost three-dozen cryoproofs SpaceX has completed with more than a dozen other Starship, booster, and test tank prototypes over the last two years, though, Ship 20’s first major test still has some oddities.
Historically, every cryoproof of a full Starship prototype has been visually unique and virtually impossible to predict. Without any direct insight from SpaceX or Elon on the objectives, plan, or timeline of tests, the process of watching tests (via unofficial webcams, of course) and attempting to interpret why certain things look the way they do or what’s going on at any given moment is a bit trying to interpret eroded hieroglyphics.
At the most basic level, cryogenic tanking tests – whether with Starship, Super Heavy, or test tanks and liquid oxygen (LOx)/methane (LCH4) propellant or neutral liquid nitrogen (LN2) – are fairly simple. The vehicle is attached to pad systems, powered on, and partially or fully loaded with cryogenic fluids. Once the desired test objectives are achieved or attempted, the vehicle is then detanked (drained of propellant or LN2).
Thanks to the fact that they’re incredibly cold (-160 to -200C; -260 to -330F), the LOx/LCH4 or LN2 Starships are filled with quickly chill the thin steel tanks containing them. With no insulation to speak of, that supercooled steel then freezes water vapor out of the humid South Texas air, creating a layer of frost/ice that generally follows the level of the cryogenic liquids in Starship’s tanks. Throughout that process, those cryogenic liquids inevitably come into contact with ambient-temperature Starship tanks and plumbing (white-hot in comparison) and warm up, boiling off into gas as a result.
A gaseous chemical is far less dense than its liquid form, meaning that the pressure inside Starship’s fixed tanks can rapidly become unmanageable after even a small amount of boiloff. To maintain the correct tank pressures, Starship – like all other rockets – occasionally vents off the gas that forms. And thus, the two main methods of interpreting the hieroglyphics that are cryoproof tests: frost levels and venting.
Compared to earlier prototypes, Starship S20’s first cryoproof has been… unusual. Most notably, SpaceX began loading the rocket with liquid nitrogen around 8pm CDT. Its LOx (bottom) and CH4 (top) tanks were then slowly filled to around 30-50% of their full volume over the next hour. However, rather than detanking, SpaceX then partially drained the methane tank but filled the LOx tank further before leaving the LOx tank more or less fully filled for more than two hours, occasionally topping it off with fresh liquid nitrogen.
Then, almost four hours after LN2 loading began, Starship performed several massive vents. Ordinarily, given the hours of testing prior, those vents would have assuredly been detank vents – effectively depressurizing Starship’s tanks as they’re drained of fluid. However, those vents instead coincided with the rapid loading of one or several hundred more tons of LN2, seemingly topping off Starship S20 in the process. Around that point, it’s possible that SpaceX began the pressure testing portion of Ship 20’s cryoproof, (mostly) closing the rocket’s vents and allowing the pressure to gradually increase to flight levels (and maybe even higher).
Many, many months ago, when SpaceX was deep into cryoproofing the first full-size Starship prototypes, Musk revealed an operating pressure goal of 6 bar (~90 psi). Ships were eventually successfully tested above 8 bar (~115 psi), giving Starship a healthy ~30% safety margin. As the first orbital-class Starship prototype, Ship 20 likely needs to hit those tank pressures more so than any ship before it to have a shot at surviving its orbital launch debut and orbital-velocity reentry attempt.
Beyond the basics of cryoproofing, Starship S20 also marked a crucial step forward on September 29th/30th, becoming the first ship to complete a cryoproof test with a full heat shield installed. While it’s impossible to judge exactly how well S20’s ~15,000-tile heat shield performed, views from public webcams showed no obvious signs of tiles shattering and falling off as Starship repeatedly cooled and warmed – contracting and expanding as a result. Additionally, still in contact with the air, the steel tank skin under a majority of Ship 20’s tiles would have likely covered itself in a layer of frost and ice, but the heat shield appeared to handle that invisible change without issue.
It’s possible that dozens or hundreds of tiles bumped together and chipped or cracked in a manner too subtle to be visible on LabPadre or NASASpaceflight webcasts, but that can only be confirmed or denied when the road reopens and local photographers can capture higher-resolution views of Starship. For now, it appears that Ship 20’s first cryoproof was highly successful, hopefully opening the door for Raptor installation and static fire testing in the near future. Stay tuned for more!
Update: As is almost tradition by now, SpaceX CEO Elon Musk didn’t take long to tweet about the results of Starship S20’s first cryoproof, confirming that the “proof was good!”
Tesla has launched a direct campaign targeting its customers in New Jersey, sending emails that warn of pending legislation that could effectively block true driverless technology in the state.
The email focuses on Senate Bill S.1677 and Assembly Bill A.3968, measures intended to create a three-year autonomous vehicle pilot program but laden with requirements that Tesla argues make unsupervised Robotaxis impossible.
Tesla is sending out this email to New Jersey Tesla owners, warning them that NJ could block autonomous vehicles, and to take action.
“Proposed legislation moving through Trenton right now would impose restrictions so severe that true driverless deployment would remain illegal.… pic.twitter.com/2bmY646AUL
— Sawyer Merritt (@SawyerMerritt) June 16, 2026
According to the email, the bills impose “restrictions so severe that true driverless deployment would remain illegal.” Specific hurdles include mandates for human safety drivers during operations, multimillion-dollar insurance minimums, reportedly $5 million, and thresholds like 100,000 miles of demonstrated safe autonomous driving before any driverless approval.
Tesla contends these are arbitrary barriers that ignore real-world performance data and favor entrenched competitors over innovative technologies like its Full Self-Driving (FSD) system.
The push comes as Tesla has started expanding Robotaxi operations in states like Texas, where unsupervised vehicles are already providing rides in several cities. New Jersey, by contrast, risks falling behind. The company highlights in the email communication that more than 94 percent of serious crashes result from human error, meaning impairment, distraction, or fatigue. These are all problems that Robotaxis eliminate entirely.
In 2025, New Jersey recorded 582 traffic deaths, underscoring the human cost of delayed adoption.
Tesla’s outreach stresses the transformative potential of robotaxis. For families, they could offer safer school runs without drowsy or distracted drivers. For seniors and people with disabilities, robotaxis promise independence and reliable mobility.
In areas with limited public transit, they could deliver affordable, on-demand transportation, reducing congestion, emissions, and overall transportation costs. Economically, the company warns that restrictive rules could cost New Jersey jobs, innovation investment, and billions in potential growth as autonomous ride-hailing scales elsewhere.
Supporters of the legislation, including Sen. Andrew Zwicker, describe the pilot as a cautious framework with strong safety oversight, including incident reporting, expert task forces, and restrictions in sensitive zones like school areas. They view it as balancing innovation with public protection.
Tesla and pro-AV advocates counter that the bill lacks technology neutrality, creates insurmountable entry barriers for commercial deployment, and prioritizes process over outcomes — effectively functioning as a de facto ban on services like Robotaxi.
This latest clash echoes Tesla’s past battles in New Jersey over direct vehicle sales. The email directs owners to Tesla’s advocacy platform, where they can send customized messages to legislators calling for amendments: outcome-based safety standards, open competition, and clear pathways for fully driverless commercial operations.
As hearings approach, Tesla’s campaign frames the issue as a choice between protecting the status quo and embracing life-saving progress. With robotaxi technology already proving itself in permissive states, New Jersey owners are being asked to ensure their state doesn’t lock out the future of transportation.
Turn-by-turn navigation is not new technology.
For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.
Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.
Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.
Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.
But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.
This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.
More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.
It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?
Multiple Data Sources
First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.
Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.
Persistent Learning
FSD seems to struggle with persistent learning from driver interventions.
Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.
This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.
I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.
The next thing I’ve noticed, and this might be controversial, is that Nav has gotten even worse.
I think that might actually be a good thing; Tesla seems to be adjusting it. They just need to adjust it the opposite way.
The car is taking extremely strange routes to very… https://t.co/UHg3tVfNA2
— TESLARATI (@Teslarati) June 16, 2026
Reasoning, Scaling, and Intuition
Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.
Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.
Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.
Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.
Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.
A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”
Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:
“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”
🚨 A Tesla Cybertruck, which is illegal to drive in the UK due to safety concerns, has been seized by police in Greater Manchester
“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a… pic.twitter.com/cqhdPok3DM
— TESLARATI (@Teslarati) June 16, 2026
The Cybertruck in question was, according to the BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.
The Greater Manchester Police Department then added:
“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”
The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.
Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.
Tesla urges New Jersey owners to oppose new bill that could block Robotaxi
Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest
