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Do autonomous cars make us worse drivers?
Autonomous cars are coming. So is the first fatality associated with them. Statistically, that milestone should occur in the next 18 months. What will happen then?
On May 31, 2009, an Airbus 330 on its way from Rio de Janiero to Paris plunged from an altitude of 35,000 feet into the Atlantic, killing all 228 people on board. Just prior to the crash, the airplane was operating in autopilot mode. A reconstruction of the disaster revealed input from several sensors had been compromised by ice that caused them to give false readings. Updated sensors that were less susceptible to ice accumulation were waiting to be installed after the plane arrived in Paris.
Because of the false readings the autopilot system disengaged returning control to the pilots however the senior pilot was sleeping at the time. The two junior pilots were not as highly trained in high altitude flight as they might have been, partly because the use of machines to control aircraft under those conditions was the norm.
Faced with the unexpected, the pilots behaved poorly. At one point they are heard to say on the cockpit recorder, “We completely lost control of the airplane, and we don’t understand anything! We tried everything!” While they tried to rouse the sleeping senior pilot, the nose of the aircraft climbed until a stall was induced. Stall is the point at which the wings become barn doors instead of airfoils. The Airbus 330 dropped from the sky like a rock.
In his excellent story about the crash published on Vanity Fair, William Langewiesche offered this conclusion: “Automation has made it more and more unlikely that ordinary airline pilots will ever have to face a raw crisis in flight—but also more and more unlikely that they will be able to cope with such a crisis if one arises.”
The Tesla community has seen similar instances lately. The driver in Salt Lake City who accidentally activated Summon, causing his car to drive into the back of a truck. The woman on a freeway in California who rear ended a car that suddenly slowed in front of her. The man in Europe who crashed into the back of a van that had stalled in the high speed lane of a highway. He at least had the courage to admit his error. “Yes, I could have reacted sooner, but when the car slows down correctly 1,000 times, you trust it to do it the next time to. My bad.”
After each of these incidents, the tendency has been for many to defend the machine and blame the human. But in a recent article for The Guardian, author Martin Robbins says, “Combine an autopilot with a good driver, and you get an autopilot with, if not a bad driver, at least not such a good one.” He says that statistically, the time when a car operating in autonomous mode causes a fatality is rapidly approaching.
On average, a person is killed in a traffic accident in the United States once every 100 million miles. Elon Musk says Tesla’s Autopilot is half as likely to be involved in a collision as a human driver. That would suggest that somewhere around the 200 million mile mark someone will die as a result of an automobile driven by a machine.
Tesla has already passed the 100 million mile mark for cars driving in Autopilot mode and continues to log 2.6 million miles driven per day. Statistically speaking, the time when a self driving car kills somebody is rapidly approaching. And since most autonomous cars on the road are Teslas, the odds are excellent it will be a Tesla that is involved in that first fatality.
What will happen then? Robbins goes back in history to look for an answer to that question. In 1896, Bridgit Driscoll became the first person in England to be killed by a motor car. The reaction among the public and the press was a fatalistic acceptance that progress will have a price. Within a few years, the speed limit in England was raised from 8 mph — which is was when Ms. Driscoll was killed — to 20 mph. This despite the fact that thousands of road deaths were being recorded on English roads by then.
Regulators around the world are racing to catch up with the explosion of new autonomous driving technology. But Robbins concludes, “By the time they do, it’s likely that the technology will already be an accepted fact of life, its safety taken for granted by consumers, its failures written off as the fault of its error-prone human masters.”
The point is that injuries and fatalities will continue to occur as cars come to rely more and more on machines for routine driving chores. But in that transition period between now and the time when Level 4 autonomy becomes the norm — the day when cars come from the factory with no way for humans to control them directly — we need to accept that complacency and an inflated belief in the power of machines to protect us from harm may actually render us less competent behind the wheel.
We will need to remain vigilant, if for no other reason than telling a jury “It’s not my fault! The machine failed!” is not going to insulate us from the legal requirement to operate our private automobiles in a safe and prudent manner.
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Tesla piggybacks recent Supercharger feature with update that takes it further
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.
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Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it
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:
News
Tesla responds to Robotaxi skeptics with a massive move in Austin
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.
