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Your Tesla will become a humanless chauffeur, summoned via app

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Photo credit: Bob Mankoff

Your Tesla eases its way through the choked streets of Los Angeles and climbs the Sierra Nevada. It glitters with the lights of Las Vegas before continuing over to Yellowstone National Park, where the geysers blow and the buffalo stare from roadsides. Meandering through the Badlands and by Mount Rushmore, it pushes upward in elevation into the Rockies and then down to Denver. After the Tesla powers past the Midwest’s cornfields, it propels its way through Chicago’s multiple highway lanes, wedged between tractor trailers. In the final leg of the trip, the Tesla dips and zips through Pennsylvania’s rolling hills and maneuvers through the congested streets of Times Square, parking itself.

These Northern route stats: 3,241 miles in 54 hours, and your Tesla did all the driving for you. It was capable of seeing through heavy rain, fog, dust, and two cars ahead.

That’s the vision, or Tesla Vision, rather, of the not-so-distant future as announced by Tesla CEO Elon Musk during a press conference call on Wednesday, October 19. Outlining a future of self-driving cars, Musk set a goal for Tesla to make a fully autonomous road trip from Los Angeles to New York by the end of 2017. The trip would occur “without the need for a single touch” from the driver, including recharging the car’s battery. Owners would be able to Summon their vehicle, through a press of a button on an app, and the car would drive itself to wherever they are and pick them up – even if it’s across the country. The vehicle would charge on its own along the way without human intervention using something similar to the Snakebot that Tesla revealed last year.

“Our goal—  I feel pretty good about this goal — we’ll be able to do a demonstration drive of full autonomy all the way from LA to New York. So basically from a home in LA to, let’s say.  dropping you off in Times Square, in New York, having the car park itself by next year. Without the need for a single touch, including the charger.”, says Musk.

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This Level 5 “full self-driving or driverless capacity” will now be available on the 2,000 cars a week that Tesla is currently manufacturing. That means the Tesla Model S and Model X vehicles in production as well as the upcoming Model 3 will have what Musk terms “Hardware 2,” which allows for full self-driving capability at “a safety level substantially greater than that of a human driver,” according to Musk. The hardware includes:

  • 8 surround cameras which provide 360 degree visibility around the car at up to 250 meters of range;
  • 12 updated ultrasonic sensors that allow detection of both hard and soft objects at nearly twice the distance of the prior system; and,
  • a forward-facing radar with enhanced processing that provides additional data on a redundant wavelength.

The system, which has been more than a year in testing, will see continual software updates as the system learns through data collected from ‘Shadow Mode’ and self-driving algorithms are refined. Musk said that it would be some time before Tesla’s software would advance to meet capabilities of Hardware 2, so it will be disabled until it “reaches parity following full validation with Hardware 1, probably in December.” Updates are likely to occur every 2-3 months thereafter. Nonetheless, and in lieu of required regulatory approval, Musk claims that the safety level of this autonomous driving will be at least twice that of a human, or better.

Tesla’s current Autopilot system has been replaced with a newer generation ‘Enhanced Autopilot’ that will leverage the new suite of sensors to provide more precise lane keeping, lane changes without driver input, the ability to exit freeways, and an overall smoother and safer experience. Enhanced Autopilot and the Fully Self-Driving Capability, autonomous mode, is being made available through Tesla’s Model S and Model X Design Studio as optional upgrades.

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Carolyn Fortuna is a writer and researcher with a Ph.D. in education from the University of Rhode Island. She brings a social justice perspective to environmental issues. Please follow me on Twitter and Facebook and Google+

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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

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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.

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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.

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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.

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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.

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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:

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“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.

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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.

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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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