News
Tesla Model S owner reminds us of ‘Active Hood’ pedestrian safety feature
A relatively unknown Tesla safety feature called ‘Active Hood’, designed to reduce head injuries to pedestrians in the event of a frontal collision, was brought to light in a recent Model S owner’s video that attempts to capture Tesla’s Automatic Emergency Braking (AEB) in action. Active Hood which exists on European and Australian Model S vehicles uses pyrotechnics to raise the rear of the hood by several inches in order to soften the impact of a pedestrian and cyclist against a windshield during frontal impact.
Model S owner and Tesla Motors Club forum member Carspotter Daily posted a video that attempts to simulate a vehicle-pedestrian interaction. The vehicle was a first generation Autopilot vehicle under Firmware 8.0. It’s unclear whether CarSpotter was intentionally trying to trigger Tesla’s Active Hood feature or whether they were looking to test the AEB system, but despite not being able to trigger either feature the end result revealed, once again, Autopilot’s ability to detect humans. Another Tesla owner YouTuber KmanAuto first detected the pedestrian alert last November when he put a friend in front of of his moving Model S.
This type of granular detection of objects allows the vehicle to respond to potential collisions in the most appropriate way, with the objective to reduce collisions entirely. Though Active Hood was mentioned in the trailing notes at the end of the recent video, it’s not clear if the vehicle used in the video is a U.S. spec Model S or a European/Australian version that was included with that safety feature.
ALSO SEE: DIY Tesla Model S Pedestrian Alert: ‘Horn’ for the Oblivious
Active Hood is not a new feature but the fact that it has only been implemented on Tesla vehicles in select markets that mandate the technology has kept it largely under the radar. The technology was built into Tesla vehicles to comply with Euro NCAP Pedestrian Safety requirements that mandate vehicle manufacturers to maintain clearances between the hood and structural components underneath, to protect pedestrians in the event of a low to medium speed collision. These accidents often prove fatal to the pedestrian, as collisions at low to medium speeds typically cause the pedestrian’s body to fold over the hood with the head hitting the windshield.
The system was put to use in real world conditions in Australia in 2015 when someone driving a Tesla Model S collided with a kangaroo which caused the system to deploy. From what they saw after the accident, it looked like the adolescent ‘roo had a broken leg but was conscious enough after the accident to limp away which seems to indicate that it was successful in preventing immediate head trauma.
Tesla had a special challenge when designing Active Hood since the front trunk of a Model S is sealed to keep water out whereas hoods to internal combustion engine vehicles are generally vented. US Patent Application US20130076076 A1 details the specific challenges and solutions developed to allow the hood to pop up in response to an imminent collision with a pedestrian.
The English European version of the Tesla Model S manual lays out the technology in a much more user friendly format:
Active Hood
With Active Hood technology only existing on vehicles destined for the European and Australian markets, and Tesla being so aggressive about implementing safety features, the natural question is “why hasn’t Tesla made this a standard global safety feature?” An early Euro NCAP crash test video showed that Tesla began working hard at doing everything it can to avoid the accident in the first place. After all, avoiding a collision in the first place is far better for all parties involved than just mitigating what happens afterwards.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
