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Self-driving Teslas and autonomous vehicles will end traffic as we know it
We are all fascinated with autonomous driving in terms of what it can do for us. Make the elderly mobile again without endangering the rest of us with their arguably reduced reaction times, less acute hearing and vision. We dream of the day when we can sleep through a long, boring trip. Doing valuable work in what would otherwise be dead time is a plus too. One thing we haven’t talked about too much is how autonomous cars can radically reduce the congestion of our roads.
Six Inches of Separation (With All Due Respect to Kevin Bacon)
One way we can reduce highway congestion is to reduce the following distances between cars. It takes a human about four seconds to react to a car stopping ahead of us. At 60 mph, that translates to 88 feet per second or a total traveled of 352 feet before you are really starting to stop the car. Using the 2 1/2 second rule would yield 220 feet. Now if you have a car which reacts in, oh say, 1,000 nanoseconds, or a millionth of a second, some have argued that a six inch separation would be more than enough time for the computer to stop the car in time to avoid a collision. So, a non-autonomous car would take up about 220 feet of roadway per car, autonomous cars would take up roughly 20 feet per car. 220 divided by 20 yields about 11 cars per 220 feet of roadway rather than one. You’ve magically increased the carrying capacity which decreases congestion.
Platooning
This increased use of autonomy will almost certainly create “platooning” on our roads where cars headed in the same direction are pulled up within inches of the car ahead creating a “car train” of 30, 50, or more cars all traveling at high speed to a destination ahead of them. With level 5 autonomy, some have suggested that 90 mph is reasonable while remaining very safe.
So let’s do a mind experiment here. You have a 220 foot stretch of roadway which can now safely carry 1 car traveling at 60 mph. Let’s put in a platoon of 11 cars traveling at 90 mph. That 220 foot stretch of roadway at 90 mph can carry 15 cars rather than 11 because 90 is 150% of 60. You have now increased the carrying capacity of the roadway by 1500%, or put another way, it would be like the New York State Thruway had 1/15 the cars on it that it does now. Rush hour would be like driving at three in the morning.
You may say that 220 feet is a preposterous amount of road and that people routinely travel only 10 to 20 feet behind the car in front of them. My response is look at the accident statistics. Yeah, you can travel that close. You just can’t travel that close safely.
Goose it Man!
One of the arguments against high speed travel in cars has been that as you increase speed, miles per kilowatt drop radically. Wind resistance is the big thief of range. When you read about people who manage to get ridiculous miles per charge out of their Teslas you can bet that last dollar that they are driving slowly!
Here’s where we can take a lesson from NASCAR and…wait for it, GEESE! Any fan of NASCAR knows that the drivers “draft” the car in front of them to save gas. The reason is very simple. The car in front is pushing the air out of the way, and the car behind benefits from traveling at the same speed in a partial vacuum, enabling the following driver to save fuel and possibly avoid a pit stop.
Why am I talking about geese? Ever wonder why geese travel in that cool V-formation? Similar reason. They avoid the turbulence from the goose ahead and conserve energy. Being cooperative sorts they trade places with the leader, who drops back and lets the next goose in line take over the toughest place, which is the lead. That way all the geese get to where they’re going quicker and with less fatigue. In our terms, with less battery energy expended.
I foresee platooning supplemented with leader “dropback” like the geese, let’s say, every five miles, to enable very fast driving times with lower fuel/kilowatt hour consumption. This will become part of the autonomous software suite.
So, all hail the goose, and I, for one, look forward to autonomous driving because of the effect platooning will have on our drives, and the automatic increase of the carrying capacity of our roads. Cool, very cool!
Allan Honeyman
(Submitted via email to the Teslarati Network. Do you a post you’d like to share? Email it to us at info@teslarati.com)
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.
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.
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.
Tesla crosses major Unsupervised Self-Driving milestone
Tesla Robotaxi will be a 24/7 service: here’s when
