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GM’s new autonomous driving system follows Mercedes, not Tesla

Credit: GM - Cadillac Celestiq

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General Motors (GM) has announced some crucial details about its upcoming Ultra Cruise autonomous driving system.

With the mass proliferation of autonomous driving, thanks largely to Tesla, more and more companies have begun working on their own systems. This includes GM, which has already released its Super Cruise system but has now released details about its next iteration, Ultra Cruise.

In the design process of autonomous systems, two leaders with two very different design philosophies have emerged. Tesla is the first, heavily relying on AI while focusing on visual sensor systems to guide the vehicle. This has been seen most clearly in Tesla’s upcoming hardware 4, which eliminates ultra-sonic sensors, instead opting to dramatically increase the quality of the visual sensing systems around the vehicle. The second camp is currently headed by Mercedes.

Mercedes has taken the complete opposite approach to Tesla. While still relying on AI guidance, Mercedes uses a combination of three different sensor arrays, visual, ultra-sonic, and LiDAR, to help guide the vehicle.

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That takes us to GM’s Ultra Cruise, which was revealed in detail today. Much like Mercedes, GM has chosen to use three sensor arrays; visual, ultra-sonic, and LiDAR. Further emulating the premium German auto group, GM’s system “will have a 360-degree view of the vehicle,” according to the automaker.

According to GM, this architecture allows redundancy and sensor specialization, whereby each sensor group will help focus on a single task. The camera and short-range ultra-sonic radar systems focus on object detection, primarily at low speeds and in urban environments. These systems will help the vehicle detect other vehicles, traffic signals and signs, and pedestrians. At higher speeds, the long-range radar and LiDAR systems also come into play, helping to detect vehicles and road features from further away.

GM also points out that, thanks to the capabilities of radar and LiDAR systems in poor visibility conditions, the system benefits from better overall uptime. GM aims to create an autonomous driving system allowing hands-free driving in 95% of situations.

As for the Tesla approach, the leader in autonomous driving certainly has credibility in its design. According to Tesla’s blog post about removing the ultra-sonic sensor capabilities from its vehicles, “Tesla Vision” equipped vehicles perform just as well, if not better, in tests like the pedestrian automatic emergency braking (AEB) test. Though it should be noted that the lack of secondary sensors is also likely to help reduce vehicle manufacturing costs.

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Ultra Cruise will first be available on the upcoming Cadillac Celestiq. Still, with a growing number of vehicles coming with GM’s Super Cruise, it’s likely only a matter of time before the more advanced ADAS system makes its way to mass market offerings as well.

“GM’s fundamental strategy for all ADAS features, including Ultra Cruise, is safely deploying these technologies,” said Jason Ditman, GM chief engineer, Ultra Cruise. “A deep knowledge of what Ultra Cruise is capable of, along with the detailed picture provided by its sensors, will help us understand when Ultra Cruise can be engaged and when to hand control back to the driver. We believe consistent, clear operation can help build drivers’ confidence in Ultra Cruise.”

With more and more automakers entering the autonomous driving space every year, it will be interesting to see which architecture they choose to invest in. But what could prove to be the defining trait is which system performs better in the real world. And as of now, it isn’t immediately clear who the victor is.

What do you think of the article? Do you have any comments, questions, or concerns? Shoot me an email at william@teslarati.com. You can also reach me on Twitter @WilliamWritin. If you have news tips, email us at tips@teslarati.com!

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Will is an auto enthusiast, a gear head, and an EV enthusiast above all. From racing, to industry data, to the most advanced EV tech on earth, he now covers it at Teslarati.

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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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