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SpaceX's workhorse Falcon 9 rocket expected to reach major launch milestone in 2020
Hours after SpaceX launched its 240th new Starlink satellite into orbit, Elon Musk took to Twitter to cryptically reveal that the company’s workhorse Falcon 9 rocket could “reach triple digits this year” if everything goes according to plan.
Designed and built by SpaceX in the late 2000s, the Falcon 9 rocket launched for the first time in June 2010. Developed for the unfathomably low price of $300 million from clean-sheet design to first orbital launch, the original single-core Falcon 9 rocket – known as V1.0 – was about 48m (160 ft) tall, weighed 333 metric tons (735,000 lb) fully fueled, and was capable of launching almost 10.5 metric tons (23,000 lb) into low Earth orbit (LEO). Famously, when provided with Falcon 9’s basic specifications and characteristics, an independent NASA study estimated that the rocket’s development would have cost the agency anywhere from $1.7 billion to $4 billion to design and build.
NASA came to this conclusion in 2011, less than a year after Falcon 9’s first launch, and that the disconnect between the status quo held by NASA and the broader US spaceflight industry and what SpaceX tangibly achieved came to almost perfectly symbolize the rocket’s first six or so years of operations. Although SpaceX stumbled hard with two catastrophic rocket failures in June 2015 and September 2016, the company ultimately picked itself up, learned from those still-agonizing lessons, and has since shaped Falcon 9 into one of the most capable, reliable, reusable, and prolific launch vehicles ever flown. That latter characteristic – the sheer volume of launches Falcon 9 has come to represent – is what CEO Elon Musk was referring to earlier this week.
Specifically, after Wednesday’s flawless launch, Falcon 9 has now launched 80 times in its 9.5-year career, while Starlink V1 L3 marked the workhorse rocket’s 52nd consecutive success of 79 total. Impressively, while those 52 launches represent almost 65% of all of Falcon 9’s missions, SpaceX has dramatically improved the rocket’s reliability and availability over the last few years. In short, Falcon 9 has completed 52 consecutively successful launches in exactly 36 months (January 2017 to January 2020), meaning that nearly two-thirds of its lifetime launches have occurred in less than a third of the time Falcon 9 has been operational.
Put a different way, since the start of 2017, SpaceX has – on average – launched Falcon 9 more than four times (1.4 launches/month) as often as the rocket managed in its first 6.5 years of operations (1 launch every 2.7 months). Tweeting on January 29th, 2020 in response to an overview of the number of launches performed by each operational US rocket, CEO Elon Musk hinted that he believes “Falcon 9 will achieve triple digits” in 2020.
In other words, Musk thinks that SpaceX’s workhorse Falcon 9 rocket will be able to reach more than 100 lifetime launches by the end of 2020 — a feat that will require at least 20 additional Falcon 9 launches over the next 11 months. Speaking hours after SpaceX completed its third launch in January 2020 alone, it’s not hard to imagine – assuming, as Musk did, that “all goes well – that Falcon 9 will manage another 20 launches this year.
Averaged out, SpaceX has performed a launch every 9.7 days in January. Extrapolated to the rest of the year and assuming no improvement, SpaceX could theoretically perform as many as 37 launches in 2020. It’s worth noting, however, that SpaceX’s third launch of the month was ready for flight as early as January 21st but was delayed more than a week by bad weather – obviously out of the company’s control. Had weather permitted, SpaceX even had a fourth launch planned this month – a Starlink mission that is now expected sometime in early February.
In simple terms, it would take one or several major upsets to prevent Falcon 9 from reaching >100 lifetime launches later this year. Even if every single customer launch abruptly slips into 2021, SpaceX has still said that it has plans for 20-24 dedicated Starlink launches in 2020 alone, potentially singlehandedly carrying Falcon 9 over the 100-launch crest.
Falcon 9’s next launch – the fourth Starlink v1.0 mission – is currently scheduled no earlier than (NET) early February, followed by another Starlink mission later that month and Cargo Dragon’s final space station resupply mission NET March 2nd.
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Tesla has launched a direct campaign targeting its customers in New Jersey, sending emails that warn of pending legislation that could effectively block true driverless technology in the state.
The email focuses on Senate Bill S.1677 and Assembly Bill A.3968, measures intended to create a three-year autonomous vehicle pilot program but laden with requirements that Tesla argues make unsupervised Robotaxis impossible.
Tesla is sending out this email to New Jersey Tesla owners, warning them that NJ could block autonomous vehicles, and to take action.
“Proposed legislation moving through Trenton right now would impose restrictions so severe that true driverless deployment would remain illegal.… pic.twitter.com/2bmY646AUL
— Sawyer Merritt (@SawyerMerritt) June 16, 2026
According to the email, the bills impose “restrictions so severe that true driverless deployment would remain illegal.” Specific hurdles include mandates for human safety drivers during operations, multimillion-dollar insurance minimums, reportedly $5 million, and thresholds like 100,000 miles of demonstrated safe autonomous driving before any driverless approval.
Tesla contends these are arbitrary barriers that ignore real-world performance data and favor entrenched competitors over innovative technologies like its Full Self-Driving (FSD) system.
The push comes as Tesla has started expanding Robotaxi operations in states like Texas, where unsupervised vehicles are already providing rides in several cities. New Jersey, by contrast, risks falling behind. The company highlights in the email communication that more than 94 percent of serious crashes result from human error, meaning impairment, distraction, or fatigue. These are all problems that Robotaxis eliminate entirely.
In 2025, New Jersey recorded 582 traffic deaths, underscoring the human cost of delayed adoption.
Tesla’s outreach stresses the transformative potential of robotaxis. For families, they could offer safer school runs without drowsy or distracted drivers. For seniors and people with disabilities, robotaxis promise independence and reliable mobility.
In areas with limited public transit, they could deliver affordable, on-demand transportation, reducing congestion, emissions, and overall transportation costs. Economically, the company warns that restrictive rules could cost New Jersey jobs, innovation investment, and billions in potential growth as autonomous ride-hailing scales elsewhere.
Supporters of the legislation, including Sen. Andrew Zwicker, describe the pilot as a cautious framework with strong safety oversight, including incident reporting, expert task forces, and restrictions in sensitive zones like school areas. They view it as balancing innovation with public protection.
Tesla and pro-AV advocates counter that the bill lacks technology neutrality, creates insurmountable entry barriers for commercial deployment, and prioritizes process over outcomes — effectively functioning as a de facto ban on services like Robotaxi.
This latest clash echoes Tesla’s past battles in New Jersey over direct vehicle sales. The email directs owners to Tesla’s advocacy platform, where they can send customized messages to legislators calling for amendments: outcome-based safety standards, open competition, and clear pathways for fully driverless commercial operations.
As hearings approach, Tesla’s campaign frames the issue as a choice between protecting the status quo and embracing life-saving progress. With robotaxi technology already proving itself in permissive states, New Jersey owners are being asked to ensure their state doesn’t lock out the future of transportation.
Turn-by-turn navigation is not new technology.
For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.
Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.
Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.
Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.
But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.
This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.
More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.
It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?
Multiple Data Sources
First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.
Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.
Persistent Learning
FSD seems to struggle with persistent learning from driver interventions.
Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.
This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.
I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.
The next thing I’ve noticed, and this might be controversial, is that Nav has gotten even worse.
I think that might actually be a good thing; Tesla seems to be adjusting it. They just need to adjust it the opposite way.
The car is taking extremely strange routes to very… https://t.co/UHg3tVfNA2
— TESLARATI (@Teslarati) June 16, 2026
Reasoning, Scaling, and Intuition
Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.
Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.
Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.
Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.
Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.
A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”
Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:
“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”
🚨 A Tesla Cybertruck, which is illegal to drive in the UK due to safety concerns, has been seized by police in Greater Manchester
“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a… pic.twitter.com/cqhdPok3DM
— TESLARATI (@Teslarati) June 16, 2026
The Cybertruck in question was, according to the BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.
The Greater Manchester Police Department then added:
“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”
The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.
Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.
Tesla urges New Jersey owners to oppose new bill that could block Robotaxi
Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest
