Connect with us

News

NHTSA says your Tesla can’t be this quiet starting Sept., 2019

Published

on

We at Teslarati are all in favor of making vehicles as safe as possible. Indeed, in our research and analysis of Teslas, we were proud early on in 2013 when the National Highway Traffic Safety Administration (NHTSA) awarded the Tesla Model S a 5-star safety rating, not just overall, but in every subcategory without exception. It was so safe, in fact, that the all-electric sedan broke the testing equipment at an independent commercial facility. Fast-forward to 2015. The Model X was the first SUV to be five-star in every category, according to Tesla CEO Elon Musk. It even won the prestigious Golden Steering Wheel (Das Goldene Lenkrad) award for best SUV this year.

Safety is important and should be primary to any driving situation. It should prevail over luxury features, style, and even comfort. However, a new NHTSA regulation that purports to target safety in its language is little more than a superficial gesture within a larger framework of driver, passenger, and pedestrian concerns.

Federal Motor Vehicle Safety Standard No. 141, which will begin on September 1, 2019, requires all newly manufactured hybrid and electric light-duty vehicles to make an audible noise at speeds below 19 mph. The sound requirement has been designed to help pedestrians who are blind, have low vision, cyclists, and other pedestrians to detect the presence, direction, and location of hybrids and EVs traveling at low speeds. At higher speeds, the sound alert will not be required because other factors, such as tire and wind noise, seem to provide adequate audible warning to pedestrians and will not be the subject of this regulation.

“We all depend on our senses to alert us to possible danger,” said U.S. Transportation Secretary Anthony Foxx. “With more, quieter hybrid and electrical cars on the road, the ability for all pedestrians to hear as well as see the cars becomes an important factor of reducing the risk of possible crashes and improving safety.”

Creating a social environment in which all individuals — especially those with disabilities, underrepresented groups, children, and the elderly — are physically and psychologically welcomed and safe is absolutely paramount to a healthy community. Manufacturers and drivers of hybrids and EVs do have a responsibility to contribute to such an environment.

Advertisement
-->

Yet, clearly, we have a generation who has been accustomed to the sounds and smells of internal combustion engines. Wouldn’t driver and pedestrian education be a more efficacious way to ensure that hybrids and EVs do not pose a safety threat? Daniel Kahneman’s (2013) work, Thinking Fast and Slow, suggests that innovative products require a higher degree of learning than existing products. Education to help EV drivers and individuals who do not have personal access to hybrids and EVS, thus, who have not built in conscious mechanisms toward the awareness of hybrids and EVs in traffic, would have longer lasting and more permanent results.

Making the case for educating pedestrians

As the general population increases its awareness of the risks of pollution to both health and the environment, the internal combustion engine has become less desirable. As a result, battery-powered, fuel-cell electric, and hybrid vehicles are technologically viable alternatives to the internal combustion engine. And they’re beginning to take on a significant segment of the U.S. vehicle market.

Essentially, an internal combustion engine works like a cannon. The sound that results is formidable and part of our collective U.S. psyche. It is ingrained in our psychological expectations of what an engine should be. Electric motors, however, make very little noise compared with an internal combustion engine. Research on the safety implications of quiet electric vehicles has mostly focused on pedestrians’ acoustic perception of EVs and suggests that EVs compromise traffic safety. However, Cocran & Krems‘ 2013 research determined that, based on gained individual experience, drivers adjust their evaluation of noise-related hazards. Some statistical observation studies in literature indicate that hybrid or EV drivers intend to be more careful, less risk takers in traffic (Horswill and Coster 2002). Thus, it makes sense to increase the awareness factors for everyone — EV drivers and pedestrians — to create more robust safe traffic situations when EVs are added to the vehicle mix.

Adding to the sound mix

Principles to increase awareness of hybrids and EVs have generally focused on alerts, or sounds that indicate the presence of an EV. Other principles, such as orientation mechanisms, which make it possible to determine where the vehicle is located, roughly how fast it is going, and whether it is moving toward or away from the listener, extend beyond mere white or overt noises.

Education transcends any of these physical additions to a hybrid or EV. Hybrid and EV drivers as well as pedestrians should be exposed to new conceptual thinking about the place of EVs in traffic situations. Alongside the new federal safety standard that requires low speed noise, hybrid and EV automakers can build in specific educational materials to prepare their consumer base for new driving situations, which will continue to add safety awareness. With access to multiple new technologies, drivers could have multimodal educational opportunities.

Advertisement
-->
  • Audio systems could provide periodic, random reminders to increase driver awareness of pedestrians and cyclists in slow speed situations.
  • Automakers could require that drivers work through a series of interactive online tutorials that accentuate driver understanding of slow speed safety adaptations with hybrids and EVs.
  • Traditional print manuals should include dedicated sections that address slow speed driver safety decision making.
  • Before-driving checklists should include explicit instruction in slow speed situations and the possibility of pedestrian interactions.

Consumer safety groups can also assume responsibility for educating their constituents about new needs for pedestrian and cyclist awareness.

  • Cyclist advocacy organizations can provide seminars to their members during events to increase strategies for hybrid and EV slow speed situations.
  • Existing support groups for persons with visual impairment can add workshops about hybrid and EVs to empower them to anticipate potential slow speed traffic situations.
  • Minimal training standards for service animals could include special animal recognition of hybrid and EVs.
  • Traditional and highly respected elderly advocacy organizations like AARP could provide print and online materials to help a generation who grew up with internal combustion engines to accommodate strategies to recognize hybrids and EVs in traffic.

Yes, adoption and diffusion of new innovations can be a long-term, complicated process. Airbags, child safety features, exhaust gas hazard, seat belts, and driver assist technologies currently provide hybrid and EV drivers with a toolkit of pedestrian safety measures. But we want more than to prevent what NHTSA says is about 2,400 pedestrian injuries each year that occur during low speed hybrid or EV/ pedestrian interactions.  We want to create a cultural climate in which a social vehicular knowledge base extends well beyond the internal combustion engine.

Carolyn Fortuna is a writer and researcher with a Ph.D. in education from the University of Rhode Island. She brings a social justice perspective to environmental issues. Please follow me on Twitter and Facebook and Google+

Advertisement
Comments

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.” 

Published

on

Credit: @BLKMDL3/X

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. 

Advertisement
-->

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.”

Continue Reading

News

Tesla earns top honors at MotorTrend’s SDV Innovator Awards

MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

Published

on

Credit: Tesla China

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.

Advertisement
-->

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.

Continue Reading

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.

Published

on

Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

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.

Advertisement
-->

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.

Continue Reading