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Self-driving Teslas and autonomous vehicles will end traffic as we know it

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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.

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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.

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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)

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Tesla AI team burns the Christmas midnight oil by releasing FSD v14.2.2.1

The update was released just a day after FSD v14.2.2 started rolling out to customers. 

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Credit: Grok

Tesla is burning the midnight oil this Christmas, with the Tesla AI team quietly rolling out Full Self-Driving (Supervised) v14.2.2.1 just a day after FSD v14.2.2 started rolling out to customers. 

Tesla owner shares insights on FSD v14.2.2.1

Longtime Tesla owner and FSD tester @BLKMDL3 shared some insights following several drives with FSD v14.2.2.1 in rainy Los Angeles conditions with standing water and faded lane lines. He reported zero steering hesitation or stutter, confident lane changes, and maneuvers executed with precision that evoked the performance of Tesla’s driverless Robotaxis in Austin.

Parking performance impressed, with most spots nailed perfectly, including tight, sharp turns, in single attempts without shaky steering. One minor offset happened only due to another vehicle that was parked over the line, which FSD accommodated by a few extra inches. In rain that typically erases road markings, FSD visualized lanes and turn lines better than humans, positioning itself flawlessly when entering new streets as well.

“Took it up a dark, wet, and twisty canyon road up and down the hill tonight and it went very well as to be expected. Stayed centered in the lane, kept speed well and gives a confidence inspiring steering feel where it handles these curvy roads better than the majority of human drivers,” the Tesla owner wrote in a post on X.

Tesla’s FSD v14.2.2 update

Just a day before FSD v14.2.2.1’s release, Tesla rolled out FSD v14.2.2, which was focused on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing. According to the update’s release notes, FSD v14.2.2 upgrades the vision encoder neural network with higher resolution features, enhancing detection of emergency vehicles, road obstacles, and human gestures.

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New Arrival Options also allowed users to select preferred drop-off styles, such as Parking Lot, Street, Driveway, Parking Garage, or Curbside, with the navigation pin automatically adjusting to the ideal spot. Other refinements include pulling over for emergency vehicles, real-time vision-based detours for blocked roads, improved gate and debris handling, and Speed Profiles for customized driving styles.

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Elon Musk

Elon Musk’s Grok records lowest hallucination rate in AI reliability study

Grok achieved an 8% hallucination rate, 4.5 customer rating, 3.5 consistency, and 0.07% downtime, resulting in an overall risk score of just 6.

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UK Government, CC BY 2.0 , via Wikimedia Commons

A December 2025 study by casino games aggregator Relum has identified Elon Musk’s Grok as one of the most reliable AI chatbots for workplace use, boasting the lowest hallucination rate at just 8% among the 10 major models tested. 

In comparison, market leader ChatGPT registered one of the highest hallucination rates at 35%, just behind Google’s Gemini, which registered a high hallucination rate of 38%. The findings highlight Grok’s factual prowess despite the AI model’s lower market visibility.

Grok tops hallucination metric

The research evaluated chatbots on hallucination rate, customer ratings, response consistency, and downtime rate. The chatbots were then assigned a reliability risk score from 0 to 99, with higher scores indicating bigger problems.

Grok achieved an 8% hallucination rate, 4.5 customer rating, 3.5 consistency, and 0.07% downtime, resulting in an overall risk score of just 6. DeepSeek followed closely with 14% hallucinations and zero downtime for a stellar risk score of 4. ChatGPT’s high hallucination and downtime rates gave it the top risk score of 99, followed by Claude and Meta AI, which earned reliability risk scores of 75 and 70, respectively. 

Why low hallucinations matter

Relum Chief Product Officer Razvan-Lucian Haiduc shared his thoughts about the study’s findings. “About 65% of US companies now use AI chatbots in their daily work, and nearly 45% of employees admit they’ve shared sensitive company information with these tools. These numbers show well how important chatbots have become in everyday work. 

“Dependence on AI tools will likely increase even more, so companies should choose their chatbots based on how reliable and fit they are for their specific business needs. A chatbot that everyone uses isn’t necessarily the one that works best for your industry or gives accurate answers for your tasks.”

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In a way, the study reveals a notable gap between AI chatbots’ popularity and performance, with Grok’s low hallucination rate positioning it as a strong choice for accuracy-critical applications. This was despite the fact that Grok is not used as much by users, at least compared to more mainstream AI applications such as ChatGPT. 

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Tesla (TSLA) receives “Buy” rating and $551 PT from Canaccord Genuity

He also maintained a “Buy” rating for TSLA stock over the company’s improving long-term outlook, which is driven by autonomy and robotics.

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Credit: Tesla China

Canaccord Genuity analyst George Gianarikas raised his Tesla (NASDAQ:TSLA) price target from $482 to $551. He also maintained a “Buy” rating for TSLA stock over the company’s improving long-term outlook, which is driven by autonomy and robotics. 

The analyst’s updated note

Gianarikas lowered his 4Q25 delivery estimates but pointed to several positive factors in the Tesla story. He noted that EV adoption in emerging markets is gaining pace, and progress in FSD and the Robotaxi rollout in 2026 represent major upside drivers. Further progress in the Optimus program next year could also add more momentum for the electric vehicle maker. 

“Overall, yes, 4Q25 delivery expectations are being revised lower. However, the reset in the US EV market is laying the groundwork for a more durable and attractive long-term demand environment. 

“At the same time, EV penetration in emerging markets is accelerating, reinforcing Tesla’s potential multi‑year growth runway beyond the US. Global progress in FSD and the anticipated rollout of a larger robotaxi fleet in 2026 are increasingly important components of the Tesla equity story and could provide sentiment tailwinds,” the analyst wrote. 

Tesla’s busy 2026

The upcoming year would be a busy one for Tesla, considering the company’s plans and targets. The autonomous two-seat Cybercab has been confirmed to start production sometime in Q2 2026, as per Elon Musk during the 2025 Annual Shareholder Meeting.

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Apart from this, Tesla is also expected to unveil the next-generation Roadster on April 1, 2026. Tesla is also expected to start high-volume production of the Tesla Semi in Nevada next year. 

Apart from vehicle launches, Tesla has expressed its intentions to significantly ramp the rollout of FSD to several regions worldwide, such as Europe. Plans are also underway to launch more Robotaxi networks in several more key areas across the United States.

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