Tesla FSD version 10.69.2.3 rolled out shortly after AI Day. The latest update of Tesla’s Full Self Driving software delivers minor bug fixes. Some testers have received v10.69.2.3 and shared their observations with Teslarati.
As previously noted, 10.69.2.3 is a relatively small update that addresses some minor bugs in FSD Beta. As it sometimes goes with software bug fixes, some Beta testers mentioned a new issue in the latest version that appeared to be a step or two backward.
Road Obstacle Detection Issues
A few testers in Tesla’s FSD Beta Program reported experiencing road obstacle detection issues when their vehicles would not register particular objects in their path or directly ahead.
For instance, beta tester Jonathan shared that his vehicle did not recognize or avoid dead animals on the road. Another beta tester experienced similar issues with gates in his community.
“One day coming back from work I decided to see if it can get me close to the proximity of my house. I live in a gated community. The vehicle made the turn into the drive entry of the community which has two swing gates. Vehicle was almost going to go through the closed gates,” FSD Beta user Sean shared with Teslarati. “I had to tap the breaks and override the system to make it stop. It didn’t see the gates as obstacles or road blocks. I have tried this a couple of times during daylight and night time and result is the same.”
After Tesla released v10.69.2.2, a few beta testers observed that their vehicles recognized and avoided construction work sites and similar obstacles on the road.
Left and Right Turns
A couple of beta testers mentioned issues with left and right turns, specifically during intersections. The most prominent issue FSD Tesla drivers raised about turns was their cars’ hesitation during intersections. Testers highlighted that their cars’ hesitation during intersections isn’t really a big issue until they consider the other drivers on the road.
“Hesitates too long at intersections presumably trying to determine if/when it’s safe to proceed. This only matters to me when there are cars behind me. I feel intense pressure to push the car through (and I do). Humans do not have patience to wait on its time-table,” noted Terry, another FSD Beta tester.
FSD Beta user Dr. Rahaman made similar observations. He noted that his Tesla would creep forward after stopping at an intersection on a red light and would take a left or right turn too slowly, sometimes irritating the drivers behind him. Dr. Rahaman specifically observed that his car entered left turn lanes late without a signal. In the past, the Tesla owner has noted that the car’s turn signals sporadically turn off and on at some intersections or turns.
Lane Selection Issues
Tesla FSD v.10.69.2.3 doesn’t appear to address the largest issue multiple testers have pointed out over the past few weeks: lane selection. One beta tester seemed to sum up the sentiments most drivers in the Tesla FSD program have regarding lane selection.
“Lane selection sometimes just plain wrong and dumb. Causes driving task to be harder for itself than it needs to be because it realizes (eventually, usually) it’s in the wrong lane too late and then has to get over which is harder with traffic and unlike a human who can gesture, the car can give no such signals as to its self-made predicament,” the tester commented.
“Also, it sometimes gets into turn lane just late enough that cars behind me assume I’m continuing straight and swoop in behind me and get over immediately causing it to be even harder for my car to get over into that lane now because all slots are occupied and the road is about to end at a light,” he added.
Other Issues
Some other less prominent issues that a few FSD Beta testers have noted are listed below.
1. Lane Positioning – The car hugs the double yellow lines too closely on narrow roads or sticks to the middle of the road when no lines are present.
2. Wide turns – The Tesla car takes wide turns, far from the curb. One tester observed that his car risked hitting the guard rails and other obstacles with its wide turn.
3. Turn Lane Issues – The car still mistakes turn lanes for driving lanes
Some testers still report experiencing phantom braking and jerkiness while taking turns. However, the one observation that seems to stick out among others came from beta tester Neeraj.
“Drives as if everyone is going to follow the rules 100% and is not accommodating or accounting for those who may not be going 100% as they should,” he said about FSD Beta.
FSD Beta still has a ways to go before 100% autonomous version rolls out to the general public. Observations and tests from beta testers help Tesla improve FSD. Elon Musk teased more significant improvements in the next update, 10.69.3. Tesla hopes to release a ‘supervised’ FSD version by the end of the year.
Have you tried out FSD Beta 10.69.2.3 yet? I’d like to hear from you! Contact me at maria@teslarati.com or via Twitter @Writer_01001101.
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Tesla crosses major Unsupervised Self-Driving milestone
Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.
Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.
The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.
In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.

Credit: Tesla
Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.
The company has not released a city-by-city breakdown of the one million unsupervised miles.
The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.
Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.
The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.

Credit: Tesla
Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.
The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.
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Tesla Robotaxi will be a 24/7 service: here’s when
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
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Tesla Full Self-Driving will now overtake manual driving to avoid disaster
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.