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Rivian’s full self-driving suite is designed to ignore an inattentive driver’s input
Rivian’s CEO RJ Scaringe has teased Jurassic Park-style self-driving tours with the company’s all-electric R1T pickup truck and R1S SUV several times now, but specific details on the car maker’s autonomy approach have been few and far between. Oliver Jeromin, Rivian’s Associate Director of Self-Driving, recently shed some light on the matter during an interview with TechCrunch.
“We want to embrace the challenge,” Jeromin said in response to a question over Rivian’s goal of bringing Level 3 autonomous driving to its vehicles versus other approaches. “There are mobility companies that are working on Level 4, and they’re looking at it kind of from the top down, coming from 4 or 5 for more fleet applications possibly… We want to get a feature into our customers hands sooner than possibly some of those other systems might be fully vetted,” he said.
Rivian’s electric lineup will enable this type of self-driving capability using a suite of cameras, radar, ultrasonic sensors, high-precision GPS technologies, and two cleverly-placed LiDAR. Such features are similar to those found in Tesla’s cars for the same purpose; however, where the two companies differ at the moment is notable. Rivian’s system is being developed to have a two-part monitoring system determining its full self-driving suite’s behavior based on driver input rather than a single requirement for hands to be on the steering wheel.
“We’re building a driver-monitoring system so it’s not just one sensor like a torque input sensor – like if a driver actually wants to disengage the longitudinal and lateral controller,” Jeromin explained. “There going to be a driver-monitoring camera, and there’s also going to be hands-on wheel sensors.”
In other words, Rivian’s full self-driving system will ignore driver input unless it is determined to be intentional. A Level 3 self-driving system can handle most aspects of driving, so if a driver wants their vehicle to behave differently than its programming is carrying out, the car will use the camera and sensors in the cabin to determine whether to proceed. If, say, the wheel is bumped from the driver shifting around in their seat for some reason, the safety procedures will know it was an accident.
“It’s really trying to determine the driver’s intention because if…you inadvertently give the steering input to the steering controller…the driver monitoring camera will see that you’re not looking at the road, and you also don’t have both hands on the wheel,” Jeromin clarified. “So, we’ll have to ignore that input from the human to understand that they’re not intending to change lanes. They’re actually just doing something else while the vehicle is in control.”
Tesla has also installed cameras to monitor activity in vehicle cabins, but the purpose isn’t exactly to monitor the driver’s intentions. Rather, Tesla Network passengers will be recorded to ensure any damages caused can be remedied. “It’s there for when we start competing with Uber/Lyft & people allow their car to earn money for them as part of the Tesla shared autonomy fleet. In case someone messes up your car, you can check the video,” CEO Elon Musk replied on Twitter to a Tesla owner’s inquiry about the tiny camera inside the rear view mirror. “Also, it can be used to supplement cameras on outside of vehicle, as it can see through 2nd side windows & rear window…Only external cameras are being used right now, so internal is not enabled. When it is enabled, we’ll add a setting to disable internal camera.”
As Rivian continues to develop its manufacturing process to bring the R1S and R1T to market, it will be interesting to also see what differences and similarities the car maker will have with other companies working on full self-driving vehicle software. Tesla has billions of miles in Autopilot-driven customer data to use for training of its self-driving program, so perhaps Rivian will eventually share its plan to close the gap.
Watch TechCrunch’s full interview with Rivian’s staff below:
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
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:
Supercharger update now shows type of Tesla at charger as well.
Pretty cool. pic.twitter.com/J3NRSIgM0m
— DennisCW | wen my L (@DennisCW_) June 2, 2026
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.
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.
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.
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:
Roughly :31 between first touching the center screen and getting the first nag
— TESLARATI (@Teslarati) June 3, 2026
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.
Here’s an 80-second phone nag test on Tesla FSD v14.3.3.
No alerts, no nagging, no annoyance. https://t.co/1dxvTOw5Cn pic.twitter.com/vYViFpjfoK
— TESLARATI (@Teslarati) May 29, 2026
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:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nags on Mad Max https://t.co/qZALU2OujY pic.twitter.com/XddOJ0D47x
— TESLARATI (@Teslarati) June 3, 2026
As well as adjusting Navigation, when I received two nags:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nag while adjusting navigation
Two nags here https://t.co/qZALU2OujY pic.twitter.com/xa3dtaDG1L
— TESLARATI (@Teslarati) June 3, 2026
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:
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:
Unsupervised Robotaxi now in the entire Austin Metro area https://t.co/eXNBdarvVS
— Tesla Robotaxi (@robotaxi) June 3, 2026
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.
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.
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.
Tesla piggybacks recent Supercharger feature with update that takes it further
Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it
