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SpaceX will host Hyperloop Pod Competition next week, Jan 27-29, 2017
Get ready to see Hyperloop concept pods fire through the 1-mile test track located outside of SpaceX and Tesla’s Design Studio in Hawthorne, California, next week between January 27-29. Elon Musk and SpaceX first unveiled the idea for a new high-speed ground transport system called the Hyperloop on August 12, 2013 with the publication of a white paper, the Hyperloop Alpha Preliminary Design Study. SpaceX’s sponsored Hyperloop Pod Competition is an incentive prize competition created to inspire university students and independent engineering teams to design and build a subscale prototype transport vehicle (a “Hyperloop pod”) that will demonstrate technical feasibility of various aspects of the high speed transportation concept. To support this competition, SpaceX has constructed a test track outside of its headquarters which we had the opportunity to see during early construction last year.
There are three judging phases in the Hyperloop Pod competition: a design competition that was held in January 2016 and an on-track competition to be held January 27–29, 2017 (Competition Weekend I), followed by a Summer 2017 (Competition Weekend II). The original specification for the Competition Basic for the Design Weekend and the competition Weekend I, though no longer available at SpaceX, can still be found online.
DESIGN WEEKEND
The Design weekend was held in January 2016 at Texas A&M University. Awards were given in three categories:
SUBSYSTEM
Best Overall Subsystem Award: Auburn University | Auburn University Hyperloop Team.
DESIGN ONLY
Top Design Concept Award: Universitat Politècnica de Valencia | Makers UPV Team
DESIGN AND BUILD CATEGORY OVERALL
Massachusetts Institute of Technology | MIT Hyperloop Team
MIT Hyperloop Team’s design was awarded the “Best Overall Design Award”, among the 23 designs selected to move to the prototype stage. The design proposes a 250 kg (551 lb) pod with a carbon fiber and polycarbonate sheet exterior. It is elevated by a passive magnetic levitation system comprising 20 neodymium magnets that will maintain a 15 mm (0.6 in) distance above the track. The team says with air pressure at 140 Pascals, the pod could accelerate at 2.4 G and have 2 Newton aerodynamic drag when traveling at 110 m/s. The design includes a fail-safe braking system that automatically halts the pod should the actuators or computers fail, and low speed emergency drive wheels that can move the pod 1 m/s. Delft Hyperloop received a “Pod Innovation Award”, while Badgerloop at University of Wisconsin, Madison, Hyperloop at Virginia Tech, and HyperXite at UC Irvine each received a “Pod Technical Excellence Award.” The full list of Awards and news clips from the Design Weekend can be found at the Texas A&M University Engineering web site. Besides the winning teams, several other teams were invited to compete in the upcoming Competition Weekend I from the Design and Build category:
- rLoop (Non-student team)
- University of Waterloo | uWaterloo Hyperloop
- University of Washington | UWashington Hyperloop
- University of Toronto | University of Toronto
- University of Maryland and Rutgers University | RUMD Loop
- University of Florida | GatorLoop
- University of of Colorado, Denver | Team HyperLynx
- University of Cincinnati | Hyperloop UC
- University of California, Santa Barbara | UCSB Hyperloop
- University of California, Berkeley | bLoop
- Texas A&M University | TAMU Aerospace Hyperloop
- Technical University of Munich | WARR Hyperloop
- Purdue University | Purdue Hyperloop Design Team
- Oral Roberts University | Codex
- Lehigh University | Lehigh Hyperloop
- Keio University | Keio Alpha
- Drexel University | Drexel Hyperloop
- Carnegie Mellon University | Carnegie Mellon Hyperloop
In February 3, 2016 eight more teams advanced to Competition Weekend I.
- Cornell University + Harvey Mudd College + University of Michigan + Northeastern University + Memorial University of Newfoundland(Canada) + Princeton University | OpenLoop
- Louisiana State University | Bayou Bengals
- New York University | NYU Hyperloop
- RMIT University | VicHyper
- John’s High School | HyperLift
- University of Illinois at Urbana-Champaign | Illini Hyperloop
- University of Southern California | USC Hyperloop
- University of Wisconsin, Milwaukee | Mercury Three
In the end, 30 of the 115 teams that submitted designs in January 2016 were selected to build hardware to compete in Competition Weekend I. There were more than 1,000 applicants at earlier stages of the competition.
JUDGING CRITERIA
Originally, the second Phase of the competition was supposed to involve competitive runs in the Hyperloop test track to be awarded based on various classes (fully functional pod, susbsystem test pod, etc.) and pod mass. This phase of the competition was renamed“Competition Weekend I,” when SpaceX added a third phase of the competition, Competition Weekend II. The original SpaceX Hyperloop Pod Competition – Rules and Requirements for Weekend I can be seen at the end of this article. We’ve embedded a copy of the original document from SpaceX.
The Judging Criteria are listed in the document, and involve scoring in 4 different categories, for a maximum overall total of 2500 points.
- Category 1: Final Design and Construction (500 points)
- Category 2: Safety and Reliability (500 points)
- Category 3: Performance in Operations (500 points)
- Category 4: Performance in Flight (1000 points)
Competition Weekend I Judging Criteria – Source: SpaceX
HYPERLOOP TEST TRACK
AECOM, a company that has designed and built some of the world’s most impressive transportation systems, was selected to design and build the world’s first Hyperloop test track as part of the pod competition hosted by SpaceX
SpaceX Hyperloop Test Track (Jan.7, 2017) [Source: Teslarati via Marco Papa]
The track is a straight one-mile run on Jack Northrop Avenue, between Crenshaw Blvd. and Prairie Ave. The SpaceX Hyperloop test track — or Hypertube — was designed in 2015 and was constructed in the fall 2016, reaching its full length of one mile by October 2016. The test track’s six-foot diameter steel tube includes a non-magnetic sub-track and said to be capable of achieving 99.8 percent vacuum. The test track itself is also a prototype, where SpaceX anticipates learning from the design, build process and evaluates how to apply automated construction techniques to future Hyperloop tracks.
The Hypertube test track is designed to enable competitors who implement a wide array of designs and build pods that will test a variety of subsystem technologies that are important to new vehicle transport systems. This will include Hyperloop-specific pods—with air-bearing suspension and low-pressure compressor designs—as well as wheeled vehicle and magnetic levitation rail designs that will support a wide array of vehicle technologies to be tested. While the Design Weekend held at Texas A&M University was open to the public, it is unclear if the Competition Weekend I will be as well, or if it will be an invitation only event like many of the SpaceX and Tesla events. Several inquiries for tickets posted to the Twitter account of the Hyperloop Pod Competition went unanswered. The Official SpaceX Hyperloop Pod Competition page does not shed any light on who will be able to attend either.
HYPERLOOP POD COMPETITION II
According to SpaceX, “based on the high-quality submissions and overwhelming enthusiasm surrounding the competition, SpaceX is moving forward with a second installment of the competition: Hyperloop Pod Competition II, which will culminate in a second competition in Summer 2017 at SpaceX’s Hyperloop test track. Hyperloop Competition II will be focused on a single criterion: maximum speed. The second competition is open to new student teams interested in competing on the test track, as well as to existing student teams who have already built and tested Pods to further refine their designs.” The Competition Weekend II event will be held in the Summer 2017 at the same SpaceX Hyperloop test track.
[pdf-embedder url=”http://www.teslarati.com/wp-content/uploads/2017/01/spacex-hyperloop-competition-rules.pdf”]
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
