Connect with us

News

Tesla Hardware 4 camera ports hint at 360-degree view with no blind spots

Image Credit: @greentheonly/Twitter

Published

on

The recent leaks of Tesla’s Hardware 4 computer provided a pretty clear teaser of the upcoming changes coming to the electric vehicle maker’s Autopilot unit. While there is still much to be learned about HW4, the leaks suggest that the number of cameras in Tesla’s electric vehicles may be increased to 11. 

Hardware 4, as its name suggests, is Tesla’s next-generation Autopilot computer. Elon Musk noted during the Q4 and FY 2022 earnings call that HW4 should be capable of operating 500% to 600% safer than a human driver. The existing Hardware 3 computer being rolled out to vehicles like the Model 3 and Model Y today are equipped with Hardware 3, which Musk noted should be capable of operating 200% to 300% safer than a human driver. 

Hardware 4 and Tesla Vision

Considering the electric vehicle maker’s focus on Tesla Vision, it is pertinent for FSD and Autopilot to see and analyze road conditions very well in real-time. With this in mind, and as per the Hardware 4 leaks that were recently posted on Twitter by prolific Tesla hacker @greentheonly, it would appear that the electric vehicle maker is increasing the number of its cameras to 11. 

A look at the Hardware 4 computer would show 12 fully-populated camera connectors, with one being marked as “Spare.” Of the remaining 11, one will still be used for the cabin camera while ten will be used for the vehicle’s exterior. This is not surprising at all as the company adopts a similar system with its existing eight-camera layout for its vehicles today. 

Hardware 3 vs. Hardware 4 Cameras

For context, Tesla’s existing layout features an eight-camera setup: one above the rear license plate, one in each door pillar, three mounted on the windshield above the rearview mirror, and one mounted to each front fender. A radar unit and ultrasonic sensors were also used in the past, though Tesla phased these out as the company focused on its development of Tesla Vision. 

Advertisement

The leaked Hardware 4 images list the cameras as the following: “F-SVC,” “L-SVC,” “R-SVC,” “L-FF-Rear,” “R-FF-Rear,” “L-FF-Side,” “R-FF-Side,” “Wide,” “Main,” “Backup,” and “Selfie.” As per the Tesla hacker, the names are a bit cryptic, but based on how they are listed, one could speculate where the cameras will be placed in a Tesla equipped with a Hardware 4 computer. 

Potential Hardware 4 Camera Placements

Immediately noticeable in the leaked images are the three cameras marked “F-SVC,” “L-SVC,” and “R-SVC.” The Tesla Parts Catalog shows that “SVC” refers to vehicle bumpers, so with these in mind, it would appear that Hardware 4 would be using three bumper cameras. Considering the references to “F,” “L,” and “R” SVC placements, the Tesla hacker noted that one of the Hardware 4 cameras might be placed in the front bumper, while two may be placed on both sides of the rear bumpers for cross traffic. 

Also notable are the Hardware 4 camera slots listed as “FF.” A total of four cameras are listed with these letters: “L-FF-Rear,” “R-FF-Rear,” “L-FF-Side,” and “R-FF-Side.” The Tesla hacker speculated that “FF” might refer to “Front Fender,” which would suggest that the cameras in the pillar may be moved to the front fender. Other Tesla watchers, however, have suggested that “FF” may also mean “Front Facing,” “Full-Frame” for higher resolution images, or “Far Field.”

No Blind Spots and 360-degree-view

If the Hardware 4 leaks are accurate, it would suggest that Tesla would be increasing the number of cameras by two as it rolls out vehicles that are equipped with its new Autopilot computer. Comparing the existing camera setup in Hardware 3 and the potential setup of Hardware 4, it would appear that the new cameras will be those placed in the rear bumper. This may also suggest that the ultrasonic sensors that were phased out in the rear bumpers might be replaced with cameras. 

Considering the potential setup of the Hardware 4 cameras, it would appear that Tesla would finally be rolling out a 360-degree view of its vehicles, which is a highly-requested feature among owners. It would also mean that some blind spots in existing cars would be addressed. Overall, Hardware 4 might not just be a step up in performance; it might also be a notable step up in safety and vision. 

Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.

Advertisement

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

Advertisement
Comments

News

Tesla urges New Jersey owners to oppose new bill that could block Robotaxi

Published

on

Credit: Grok

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.

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.

Continue Reading

News

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

Published

on

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.

Continue Reading

Cybertruck

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

Published

on

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.

Continue Reading