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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.
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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
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(Submitted via email to the Teslarati Network. Do you a post you’d like to share? Email it to us at info@teslarati.com)
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
Tesla headlights have caused a recall of over 20,000 of the company’s two most popular vehicles, the Model 3 and Model Y, due to the low-beam bulb exceeding the maximum allowed intensity according to federal standards.
Tesla initiated the recall with the National Highway Traffic Safety Administration (NHTSA) this morning, stating that the low-beam output “exceeds the maximum allowed intensity in the outer upper-right and outer upper-left areas of the 10U and 90U zone, as prescribed in FMVSS No. 108.”
Tesla sourced the impacted headlights from Marelli Automotive Lighting, a Mexico-based company. The recall impacts 2020-2023 Model Y vehicles and 2017-2023 Model 3 vehicles. It is estimated that every VIN in this recall is impacted by the defect.
🚨 Tesla is recalling 20,349 2020-23 Model Y vehicles and 2017-23 Model 3 vehicles due to an excessively bright headlamp low beam.
Currently, there is no remedy plan in place, as it is still being developed. pic.twitter.com/y34cIO2U0B
— TESLARATI (@Teslarati) August 11, 2026
Typically, Tesla would remedy recalls of this nature through an Over-the-Air software update, which has been a major focus of criticism by the company and its supporters because the NHTSA still refers to it as a “recall,” even though it requires no action by the vehicle owner. The fix is shipped over the internet and downloaded to the car.
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However, there appears to be a potentially different solution for this problem. Tesla has not developed a remedy for this issue, so it could potentially be on the way. The big issue appears to be the fact that these recalled lamps are out of production, and this is an old body style for both vehicles. The headlights and front-end designs are completely different.
Tesla switched to another supplier when the affected headlight design was discontinued. It plans to begin notifying owners of their remedy options by September 15.
Tesla filed a petition protesting the recall to fix the vehicles’ headlight issue, but the NHTSA denied it. Now, Tesla will come up with a solution to fix it.
Tesla has one big financial question to answer for investors: Morgan Stanley
SpaceX AI investment gamble will make it a big winner, firm says
