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GM says Tesla can’t achieve Level 5 self-driving using Autopilot hardware

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Director of autonomous vehicle integration for General Motors, Scott Miller, thinks Tesla’s goal to build a self-driving vehicle that meets SAE’s criteria for a fully autonomous Level 5 car is not physically possible when using Autopilot hardware.

“The level of technology and knowing what it takes to do the mission, to say you can be a full level five with just cameras and radars is not physically possible,” said Miller in speaking to the Australian press about Tesla CEO Elon Musk’s goal to produce a full self-driving vehicle using Autopilot technology.

“The mission” that Miller is speaking about is Musk’s plan to demonstrate a cross-country drive from California to a parking garage in NY, in a Tesla, and achieved completely without human intervention. Miller believes that Tesla’s perception of fully autonomous self-driving doesn’t take into account the safety levels and standards defined by the SAE for Level 5 autonomy. According to the SAE’s Automated Driving Guide, Level 5 allows for “the full-time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver.”

“I think you need the right sensors and right computing package to do it. Think about it, we have LIDAR, radar and cameras on this. The reason we have that type of sensor package is that we think you need not be deeply integrated in to be level five, you should have redundancy.” says Miller.

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LEVELS OF DRIVING AUTOMATION ARE DEFINED IN NEW SAE INTERNATIONAL STANDARD J3016

“Do you really want to trust just one sensor measuring the speed of the car coming out of an intersection before you pull out? I think you need some confirmation. So, radar and LIDAR do a good job at measuring object speed, cameras do a great job at identifying objects. So, you can use the right sensor images to give you confidence in what you’re seeing, which I think is important if you’re going to put this technology out for general consumption.”

Miller adds, “Could you do it with less and be less robust? Probably. But could you do it with what’s in a current Tesla Model S? I don’t think so.”

“Could you do it with what’s in a current Tesla Model S? I don’t think so.”

The GM executive’s stance on using LiDAR in combination with radars and cameras goes completely against the grain of Musk who firmly believes that its LiDAR-less Autopilot hardware suite is capable of achieving full autonomy and at a consumer-friendly price point.

Musk reaffirmed his position that Autopilot hardware included in the latest Model S and Model X will be able to support self-driving features. “You can absolutely be superhuman with just cameras. You could probably do it 10 times better than a human with just cameras.” said Musk at TED2017.

“November or December of this year, we should be able to go all the way from a parking lot in California to a parking lot in New York with no controls touched in the entire journey.”

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Still, the majority of technologists within the autonomous driving community believes that infrared LIDAR and its ability to create complex 3D maps to support autonomous cars is crucial when it comes to reliability and safety.

General Motors recently launched its SuperCruise system on the Cadillac CT6 that allows Level 2 autonomous driving. The Detroit-based automotive giant believes that achieving Level 5 full autonomy is still 15 years away.

What do you think about GM’s comments? Is Musk’s vision for Tesla’s Full Self-Driving capabilities overly optimistic?

https://www.youtube.com/watch?v=_rxW68ADldI

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Gene has been obsessed with cars since before he could legally sit in the front seat. Writer, researcher, unofficial CS support, accountant, native suit guy when needed, and overall stick poker. He approaches every story the way he approaches a road trip: with too much enthusiasm, not enough planning, and a surprisingly good outcome. gene@teslarati.com

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Tesla piggybacks recent Supercharger feature with update that takes it further

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Credit: Tesla

Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.

This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.

The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.

Tesla supplements Holiday Update by sneaking in new Full Self-Driving version

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Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.

Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:

This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.

Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.

Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.

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Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.

In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.

As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.

With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.

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Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it

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Credit: TESLARATI

Tesla Full Self-Driving v14.3.3 driver monitoring was reportedly scaled back in recent releases, but a new version that was released in the early hours of June 3 aimed to do a better job of keeping those in control of their cars honest, according to release notes.

The release notes for FSD v14.3.3, via Software Version 2026.14.6.7 added:

“Improved driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.”

However, Tesla said this was already enabled in the first rollout of FSD v14.3.3 in late May. We tested it anyway, especially as the Standard Speed Profile seemed less-than-worried about what you were doing during operation.

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I decided to try out the Hurry and Mad Max Speed Profiles for this test, and it gave me results that I would have expected. Tesla has evidently ramped up driver monitoring based on the Speed Profile you are using to travel.

The more aggressive the Speed Profile, the more on the hook you will be for taking your attention away from the road. Our testing showed that Mad Max was less likely to allow you to do normal things like change music or adjust navigation without getting an on-screen warning or nag from the driver monitoring system.

Hurry Mode Results

On Hurry, the driver monitoring system on FSD v14.3.3, via Software Version 2026.14.6.7, was more restrictive than Standard but less restrictive than Mad Max. I found that I could scroll through music options for a considerable amount of time, more than 30 seconds:

Standard gave me about 80 seconds of phone scrolling with absolutely no nags or warnings in a previous test. It is worth noting that this was a previous branch of v14.3.3, but Standard is such a goodie-two-shoes on the road that it is my impression it would not change much.

Mad Max Results

I spent the majority of the drive on Mad Max to see how it truly reacted to the driver having their attention elsewhere. While I did do a short phone test, I am aiming to steer away from those and use the center screen. I think it is a valid criticism that the phone test is dangerous and, not to mention, illegal in Pennsylvania. Changing the navigation and music is a more reasonable, more responsible, and safer test.

With Mad Max being the fastest and most aggressive Speed Profile, I anticipated this being the quickest mode to give me an alert that I needed to look at the road. That was the case with music:

As well as adjusting Navigation, when I received two nags:

These nags were more than reasonable, and I think it’s probably good that Tesla is ramping up the driver monitoring. I do believe that it should be relatively strict across all of the Speed Profiles, especially with phone use. When using the center screen, the nag intervals should be based on the speed profile you are utilizing at the time.

These driver monitoring adjustments are a great thing to have while FSD is still under its “Supervised” moniker, but I expect Tesla to continue pushing the limits on what it will allow, especially considering CEO Elon Musk has hinted that phone use is capable with the more recent versions.

You can watch the full drive on YouTube below:

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Tesla responds to Robotaxi skeptics with a massive move in Austin

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Credit: @AdanGuajardo/X

Tesla has responded to the skeptics of its Robotaxi program by launching a massive expansion of the unsupervised program in its initial rollout city of Austin.

The company’s geofence, the enabled area of operation for rides, now covers the entire Austin Metropolitan area, an incredible move just days after media headlines attempted to discredit the ride-hailing service.

Those who have access to the Tesla Robotaxi app on their smartphones can now request a ride in any portion of the Austin Metro area. The company confirmed this on the social media platform X:

This is Tesla’s fifth expansion of the geofence, with the others occurring in July, early August, late August, and late October 2025. It has remained at that size since October 26, but Tesla has now more than doubled that size.

It is now covering the entire area, including suburbs like Pflugerville and Manor, as well as I-35 highways, Gigafactory Texas, and the Austin-Bergstrom Airport.

The move comes just days after various media outlets highlighted the small fleet size of Tesla’s Robotaxi fleet in Austin, something that is a reasonable criticism but an understandable move on the company’s part to prioritize safety.

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Tesla expands Robotaxi geofence, but not the garage

Tesla has expanded its Robotaxi geofence many times, but its fleet has remained at a relatively conservative size as the company continues to push safety as its most crucial metric.

The latest expansion is a key indicator of Tesla’s comfort level to expand the ride-hailing service. The move shows Tesla is scaling unsupervised autonomy, as it demonstrates that the company’s Full Self-Driving system has reached sufficient reliability for a broader real-world deployment, which is something the company has worked on extensively.

It also shows Tesla is game for a competition with its rivals in the autonomous ride-hailing sector. Tesla has often matched or exceeded competitors like Waymo in coverage area, despite its smaller fleet. This step highlights Tesla’s iterative, data-driven progress toward a high-margin, app-based Robotaxi network.

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It’s not the absolute largest area expansion ever, but achieving full unsupervised operations across a major metro is a key moment in the Robotaxi story. It shifts the program from limited pilot/testing toward a more mature commercial service, while gathering the miles needed for faster growth.

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