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SpaceX Falcon 9 crushes next-gen ULA Vulcan rocket on cost in first competition
The United Launch Alliance’s (ULA) next-generation Vulcan Centaur rocket appears to have made it through what could be described as its first real competition with SpaceX and its Falcon 9 workhorse.
The US Space Force (or Air Force) awarded both rockets two launch contracts each on March 9th, marking the second award under “Phase 2” of a new National Security Space Launch (NSSL; formerly Evolved Expendable Launch Vehicle or EELV) agreement. The culmination of a multi-year competition, NSSL Phase 2 calcified in late 2020 when the US military ultimately chose ULA and SpaceX as its primary launch providers for the better part of the next decade.
The final Phase 2 agreement followed Phase 1, in which the USAF committed up to $2.3 billion to assist Blue Origin, Northrop Grumman, and ULA in their efforts to develop future military launch capabilities. SpaceX submitted a proposal but didn’t win funds. Even though the ULA-SpaceX dichotomy was already a more or less fixed outcome before the competition even began, the US military still managed to dole out almost $800 million to Blue Origin and Northrop Grumman before announcing that neither provider had been selected for Phase 2.
Notably, as part of Phase 1, ULA is on track to receive nearly $1 billion in USSF/USAF aid to develop its next-generation Vulcan Centaur rocket and ensure that it meets all of the military’s exacting, unique requirements. SpaceX, on the other hand, received a sum total of $0 from that opaque slush fund to meet the exact same requirements as ULA.
For Phase 2, the US military arbitrarily split the roughly two-dozen launch contracts up for grabs into a 60/40 pile. Even more bizarrely, the USAF did everything in its power to prevent two of the three rockets it had just spent more than $1.7 billion to help develop from receiving any of those two or three-dozen available launch contracts – all but literally setting $800M of that investment on fire. Short of comical levels of blind ineptitude, verging on criminal negligence, the only possible explanation for the US military’s behavior with NSSL Phase 1 and Phase 2 is a no-holds-barred effort to guarantee that ULA and its Vulcan Centaur rocket would have zero real competition.
The arbitrary 60:40 split of the final Phase 2 contract ‘lot’ further supports that argument. A government agency objectively interested in securing the best possible value and redundancy for its taxpayer-provided money would logically exploit a $1.7B investment as much as possible instead of throwing two-thirds of its ultimate value in the trash. On its own, a block-buy scenario – even with a leading goal of selecting two providers – is fundamentally inferior to an open competition for each of the dozens of launch contracts at hand.
Further, selecting the block-buy option and failing to split those contracts 50:50 makes it even clearer that the USAF’s only steadfast NSSL Phase 2 goal was to guarantee ULA enough Vulcan launch contracts for the company to be comfortable and (most likely) not lose money on a rocket that has yet to demonstrate an ability to compete on the commercial launch market.
Amazingly, despite multiple handicaps in the form of a 60:40 contract split and what amounts to a $1B subsidy that explicitly disadvantages its only competitor, ULA’s Vulcan rocket still appears to be ~40% more expensive than SpaceX’s Falcon 9. In the latest round of NSSL Phase 2 contracts, seemingly the first in which ULA’s Vulcan Centaur rocket was selected, SpaceX’s Falcon 9 received two East Coast launch contracts worth slightly less than $160M, averaging out to less than $80M each.
Outfitted with four of a possible zero, two, four, or six strap-on solid rocket boosters (SRBs), Vulcan Centaur received two launch contracts for $224M – an average of $112M each. Assuming ULA wins exactly 60% (~15) of the Phase 2 launch contracts up for grabs and receives no more than $1 billion in USAF development funding through NSSL Phase 1, some $67 million will have to be added to the cost of each announced Vulcan launch contract to get a truly accurate picture. In the case of the rocket’s first two contracts, the real average cost of each Vulcan Centaur launch could thus be closer to $179M ($112M+$67M).
According to ULA CEO Tory Bruno, both Vulcan missions are to “high-energy orbits,” whereas a USAF official told Spaceflight Now that SpaceX’s two Falcon 9 contracts were to “lower-energy orbits.” In Vulcan’s defense, if Bruno’s “high-energy orbit” comment means a circular geostationary orbit (GEO) or a very heavy payload to an elliptical geostationary transfer orbit (GTO), it’s possible that SpaceX would have had to use Falcon Heavy to complete the same contracts. Against Falcon Heavy’s established institutional pricing and excluding ULA’s $1B Phase 1 subsidy, Vulcan Centaur is reasonably competitive.
Ultimately, even with several significant cards stacked against it, SpaceX appears likely to continue crushing entrenched competitors like ULA and Arianespace on cost while still offering performance and results equivalent to or better than even than their “next-generation” rockets.
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
