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Tesla Model Y’s revised suspension impresses car expert: ‘It was like riding on rails’
Automotive industry veteran Sandy Munro is in currently in the process of tearing down the Tesla Model Y. In a recently uploaded video, Munro delved into the vehicle’s suspension system, highlighting some of the subtle differences that Tesla made from the Model 3 to the Model Y.
Munro states that he is impressed with the new suspension of the Model Y. In an interview with Bloomberg Technology on YouTube, he says, “I thought this thing handled really well. I liked it; it was like riding on rails.”
In the recent MunroLive post, Munro highlights the similar suspension design between both the Model 3 and the Model Y, but clarifies that the two are not completely the same. One of the first differences Munro highlights is Tesla’s use of screws on the Model Y’s suspension dampers.
Previously on the Model 3, Tesla utilized a series of small bands to reinforce the sedan’s damper system. The primary function of this piece of the suspension is to quite literally “damper” the amount of bounce during travel. The damper controls the oscillation of the suspension spring and creates a less bumpy and smoother ride.
The reinforcement of the damper to the suspension system with screws creates a more robust and sturdy support. The Model 3’s damper system was subject to some complaints as per posts on the Tesla Motors Club forum, with some owners stating that their cars’ damper systems were weakening. Tesla could have reinforced the Model Y’s suspension system with screws because of the vehicle’s higher weight, as well.
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- The Tesla Model 3’s damper reinforcement, which consisted of “bands,” or zip ties. (Credit: YouTube | MunroLive)
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- The Tesla Model Y’s damper reinforcement system, which consists of screws. (Credit: YouTube | MunroLive)
Munro then commented on the “much beefier” build of the Model Y’s front suspension lower control arm, which is responsible for allowing suspension setting parts to rotate whenever the car is cornering. Tesla’s decision to create a more reliable control arm for the front suspension of the vehicle could also be due to the Model Y’s higher weight compared to the Model 3. But reasoning aside, Munro was happy with the decision to create a more robust control arm as it contributes to the Model Y’s improved suspension system.
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- Tesla Model 3’s lower control arm. (Credit: Pacific Motors)
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- The Tesla Model Y’s front lower control arm. Munro credits it as “beefier” than the Model 3’s. (Credit: YouTube | MunroLive)
In the rear suspension, there were fewer changes compared to the Model 3. The Model Y Performance that perched on top of Munro’s car lift was actually equipped with rear suspension lower control arms that were labeled as Model 3 parts. Munro states the commonality between the two parts not only suggests that Tesla had it right with the Model 3’s rear lower control arm, but that the carmaker will reduce spending money on developing or installing revised parts on its new vehicles. “This is a good idea for carmakers to use, or reuse, parts that have proven to be worthwhile,” Munro says.
The subtle changes Tesla decided to make the Model Y’s suspension system compared to the Model 3 not only increased cost-effectiveness but also improved the overall quality of the vehicle’s suspension. Munro states that a more in-depth analysis of the Model Y’s suspension will come when his team completely disassembles the car. According to this preliminary look at the system, Munro has noted drive quality and build quality improvements that have matched some of his standards so far.
Watch Sandy Munro’s first review of the Model Y’s suspension system below.
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
