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Quantum ‘compass’ technology aids in navigation without use of GPS satellites
Scientists from Imperial College London and M Squared, a photonics and quantum technology company, have created a portable quantum accelerometer which enables location tracking without the aid of GPS satellites. As demonstrated at the National Quantum Technologies Showcase 2018 in London, the device utilizes ultra-cooled atoms and lasers to measure position with precision made possible by quantum mechanics. The system is currently designed to be used for navigating large vehicles such as ships and trains, but smaller-scale devices will be available as the technology develops.
Quantum accelerator in the lab. | Credit: Imperial College London
The reliance on global navigation satellite systems such as GPS has a few significant shortcomings that the quantum accelerometer would overcome. Satellite signals can be blocked or jammed, interfering with the systems that rely on the data being provided. Threats such as electromagnetic pulse (EMP) attacks on a massive scale, now closer to reality with nuclear capability developments around the world, would cripple any technology relying on satellite systems.
The financial burden of GPS failure is also a serious consideration driving the innovation behind this device. In M Squared’s press release announcement, it was estimated that each day without GPS services in the United Kingdom would cost the country 1 billion pounds. Since it’s a self-contained system not reliant on external signals, a quantum accelerometer would not be at risk for these types of security or financial fallouts.
A close up of the quantum accelerator. | Credit: Imperial College London
Even without the consideration of electronic attacks and satellite failures, a much smaller version of this technology could overcome day-to-day problems with regular GPS use. Anyone who has ever used a map application in a city environment has likely experienced blockages from the buildings disrupting satellite signals. A quantum accelerator would calculate its position based on its high precision velocity measurements rather than GPS information, thus eliminating never-ending “recalculating” type errors that current mapping devices are prone to receive.
General accelerometers are already found in common devices like cell phones and video game controllers. Overall, they function by calculating changes in the velocity of an object (phone, controller, etc.) and that data is used for whatever its intended purpose. For location-driven applications, however, the measured position loses accuracy without feedback from external sources such as GPS. For example, after a few street turns (or less), a mapping application would need to confer with a satellite to recalculate the new position of the car in motion. The high precision of a quantum accelerometer does not have this limitation, thus eliminating the need for a GPS signal.
When atoms are cooled to ultra-cold levels, their quantum behavior emerges and can then be measured by a laser beam acting as a ruler. The team behind the quantum accelerometer device had already been developing other commercial quantum technologies prior to the current one, so when the need for arose for measuring and cooling atoms, a solution was already in place via the team’s universal laser system developed for gravity measurements. This laser both cools and measures the atoms involved in the accelerometer’s device’s movement calculations.
This quantum device is representative of the transition of quantum mechanics from the science laboratory to real-world applications. Besides navigational solutions, Professor Ed Hinds, Director of the Centre for Cold Matter at Imperial College London, described gravity measurements, mapping gravitational forces to look for minerals, and looking inside vehicles to diagnose problems as a few suggestions for other applications. “[The potential applications] …all come from the fantastic sensitivity and reliability that you can only get from these quantum systems.”
Watch the video below to see the quantum team tell more about the device.
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
