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SpaceX schedules second Starship static fire after first test ends prematurely

On January 6th, SpaceX fired up Starship SN9's three Raptor engines for the first time. (NASASpaceflight - bocachicagal)

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Update: SpaceX appears to have plans for a second triple-Raptor static fire for Starship SN9 after the rocket’s first test was cut short for unknown reasons.

Identical to previous road closure windows, SpaceX will have an opportunity to test Starship SN9 from 8 am to 5 pm CST (UTC-6) on Friday, January 8th, potentially paving the way for a high-altitude launch attempt early next week if the second static fire goes as planned. Stay tuned for updates!

In what is likely one of the last steps before SpaceX’s next high-altitude Starship launch attempt, the company appeared to successfully put Starship serial number 9 (SN9) through its first triple-Raptor static fire test.

Relatively late into a test window that opened at 8 am CST (UTC-6) but was later pushed to noon, SpaceX’s first Starship SN9 static fire attempt began in earnest around 3:15 pm CST. Signified by venting activity at the propellant farm tasked with preparing and loading liquid oxygen and methane on Starships, slight tweaks in the test flow were observed but the static fire occurred more or less when expected at 4:07 pm.

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SN9 ignited all three of its Raptors in quick succession and shut the engines down over the course of 1.5-2 seconds – extremely short relative to all previous nominal Starhopper or Starship-mounted Raptor static fires. Long-time followers immediately noted that small discrepancy, speculating that it could either have been a post-ignition abort or intentionally shortened to avoid damaging the pad’s concrete surface (an incident that’s occurred several times during recent tests).

Not long before the short static fire, SpaceX extended the end of its January 6th test window (in the form of road closure notices) from 5 pm to 8 pm. Oddly, rather than the expected response of detanking Starship and reopening the road after a successful test, SpaceX essentially recycled SN9 and began a separate test around 6 pm. The road was never reopened and a SpaceX team never headed back to the pad between the tests, implying that the company may have run into a minor hardware or software bug earlier in the day.

It’s unclear what the actual goal of the second attempt was and it’s more or less impossible to know for sure with confirmation from CEO Elon Musk. It’s possible – if unlikely – that the first static fire went exactly as planned and the follow-up test was meant to be a simple data-gathering wet dress rehearsal (WDR). Either way, after a surprise downpour briefly engulfed Starship SN9 minutes prior, the second test appeared to abort about 30 minutes into propellant conditioning and loading, precluding both a complete WDR and/or static fire.

Starship SN9 is pictured preparing for its first static fire attempt on January 3rd. (NASASpaceflight – bocachicagal)

According to a test notice received on January 6th by NASASpaceflight contributer and photographer Mary (bocachicagal), SpaceX has another test window available on January 7th in the event that Wednesday’s testing was partially unsuccessful. In a rare case, SpaceX’s hand-distributed warning for residents preceded any additional planned road closures, the last of which lifted on January 6th.

On January 5th, SpaceX received a trio of Temporary Flight Restrictions (TFRs) from the FAA that will allow the company to restrict access to nearby airspace for high-altitude Starship launch attempts on January 8th, 9th, and 10th. Lacking an unequivocally successful static fire, it’s highly unlikely – but not impossible – that Starship will be ready for a launch attempt during any of those three windows. Still, it’s safe to say that SN9 is probably less than a week away from its first flight – expected to be a carbon copy of SN8’s 12.5 km (7.8 mi) launch and landing attempt – if SpaceX can complete a full-duration static fire in the next day or two.

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Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest

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Credit: TESLARATI

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.

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.

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Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK

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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.”

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.

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Apple is developing the missing link for Tesla to get CarPlay: report

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Credit: Michał Gapiński/YouTube

A new report claims that Apple is in the process of developing what would be the missing link for Tesla to get CarPlay.

Apple and Tesla have been reportedly working together for some time to give Tesla owners the opportunity to utilize CarPlay within their vehicles. While many owners are more than happy with Tesla’s in-house UI, which is seamless, effective, and smooth, some still want CarPlay, which does have its advantages.

A report from 9to5Mac now states that a new CarPlay technology that was highlighted during the Worldwide Developers Conference (WWDC) would potentially be the bridge between Tesla and Apple. With the addition of a feature known as “Route Sharing,” which gives a navigation app the ability to share routing data with the vehicle, Tesla would be able to launch CarPlay in its vehicles, the report states.

CarPlay has not been a priority for Tesla because it has done extremely well with its in-house UI, but some drivers are just used to it. Additionally, it could improve Tesla’s subpar Navigation or offer improved app capabilities, especially with iMessage.

Route Sharing is an intended addition to CarPlay’s iteration in iOS 26.4, which was released in March:

The addition of CarPlay would undoubtedly be welcome, but at the same time, it seems like Tesla realizes it is not of the utmost priority. There are so many things that Tesla is working on currently within its own vehicles, especially attempting to solve self-driving.

Back in February, Bloomberg had reported that Tesla was still working on bringing CarPlay to its vehicles, but it had not due to app compatibility issues and incredibly low adoption rates of iOS 26.

This bottleneck could buy Tesla the proper amount of time to develop CarPlay for its vehicles. It would be a welcome addition, and could be brought on with either the Summer or Fall 2026 Software Updates.

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