News
SpaceX's latest Starship test was uneventful and that's great news for its flight debut
According to Elon Musk, SpaceX has successfully completed its latest Starship prototype test in a uniquely uneventful fashion, great news for the next-generation rocket’s next steps and first flight tests.
The SpaceX CEO revealed the news some 12 hours after the company wrapped up the Starship tank test at its Boca Chica, Texas facilities. Another excellent example of SpaceX’s preferred process of agile development, the test followed just nine days after the Starship SN01 prototype’s first cryogenic test unexpectedly unearthed a design flaw. SpaceX analyzed the results of Starship SN01’s unintentional launch debut and drew up plans to rapidly repurpose a Starship tank initially destined for the SN02 prototype.
By using existing hardware to test an upgraded iteration of the part that destroyed Starship SN01, SpaceX has now effectively retired the risk posed by that prior failure less than two weeks after it occurred. Elon Musk specifically noted that the former SN02 engine section “passed cryo pressure & engine thrust loads,” confirming that there was more to the exceptionally uneventful evening of March 8th than met the eye. While putting on much less of a show for local observers, this particular boring test is a great sign for the next few steps of SpaceX’s Starship development program.
SN2 (with thrust puck) passed cryo pressure & engine thrust load tests late last night— Elon Musk (@elonmusk) March 9, 2020
Simply put, despite successfully demonstrating that Starship’s improved “thrust puck” and engine section can survive flight-level tank pressures and the thrust of a Raptor engine, one would be hard-pressed to determine as much by inspecting the prototype that managed the feat. Such a visually uneventful test is a first for SpaceX’s post-Starhopper Starship testing, where “before” and “after” photos typically start with a shiny tank and finish with a well-distributed field of steel shrapnel.
Musk’s description of the test suggests that SpaceX’s intention with the SN02 test tank – built in just two weeks – was to stress it up to (and likely beyond) the pressures and mechanical stresses Starship engine sections will need to survive in flight. In simpler terms, they likely tried to burst the tank by pressurizing it with liquid nitrogen, a supercool cryogenic fluid. It’s unclear exactly how far SpaceX pushed the tank, but it’s safe to say that it went at least as high as past test tanks, meaning 7-8.5 bar or 100-125 psi. At a bare minimum, a test that failed to reach Starship’s minimum flight pressure of 6 bar (90 psi) would be of dubious value for the actual orbital ship.
A step further, SpaceX installed a hydraulic jack underneath the test tank in a bid to simulate the stresses it would experience with a single Raptor engine. Capable of producing approximately 150-200 tons (1500-2000 kN) of thrust, even Raptor is relatively minor compared to the Starship tank’s likely ~500 metric ton (1.1 million lb) mass. Still, the fact that the SN02 test tank survived the combination of a highly pressurized tank and the simulated thrust of a Raptor engine suggests that SpaceX is now ready for a more successful repeat of Starship SN01 testing.
Confirming those suspicions, Musk subsequently revealed that the Starship prototype integrated immediately after the SN02 test tank will likely attempt the first Raptor static fire tests and may even perform short flights further down the road. As always, SpaceX’s testing programs are fluid and likely to change as new results continuously shape the path forward, meaning that Starship SN03 could easily be destroyed during testing. Starship SN04, said by Musk to be the hopeful candidate for “longer [test] flights,” would thus be repurposed to continue SN03’s test campaign — and so on with SN05, SN06, and beyond.
Regardless, as the CEO notes, perhaps the most important aspect of all these rapid-fire tests is that SpaceX is quickly building up an impressive Starship production line. Before, during, and after SN02’s test campaign, SpaceX’s South Texas team has been simultaneously fabricating and stacking new steel rings, bulkheads, and noses for the next few Starship prototypes. As a result, Starship SN03’s tank section could be just a week or two away from complete integration, after which SpaceX will likely transport it to the launch pad to prepare for Raptor static fire testing.
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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
