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Driver-assistance tech seen as annoyance by many non-Tesla drivers
Automakers have been adding driver assistance features to new vehicles for years now, especially with the industry gearing towards self-driving technology. However, a recent J.D. Power 2019 U.S. Tech Experience Index (TXI) Study has found that many drivers see them as “nannying” annoyances and often opt to turn them off. While it doesn’t look like Tesla’s all-electric vehicles were included in the study, the results draw an interesting contrast between Autopilot and other manufacturers’ approach to similar technology.
“Automakers are spending lots of money on advanced technology development, but the constant alerts can confuse and frustrate drivers,” explained Kristin Kolodge, Executive Director of Driver Interaction & Human Machine Interface Research at J.D. Power, as quoted in the study’s summary. “The technology can’t come across as a nagging parent; no one wants to be constantly told they aren’t driving correctly.”
When it comes to lane-keeping and centering systems in particular, an average of 23% of customers with these systems complained that the alerts are annoying or bothersome. Of this group, around 61% frequently choose to disable the features. Even more telling is that out of six categories of vehicle features rated by the study, driving assistance was scored second lowest in measured owner experiences. The other categories were collision protection, smartphone mirroring, comfort and convenience, entertainment and connectivity, and navigation. The study overall was focused on owner experiences, usage, and interaction with 38 driver-centric vehicle technologies at 90 days of ownership.
The Kia Stinger scored the highest in all categories out of the vehicles rated by J.D. Power. On a 1,000-point scale, it averaged 834, the overall average being 781 and the lowest-scoring model coming in at 709. The Korean auto maker’s compact luxury sedan has a full suite of active safety features including adaptive cruise control, automatic emergency braking, blind spot warning, rear cross-traffic alert, lane keeping assist, pedestrian detection, and a driver attention alert.
Since owner satisfaction is directly tied to future purchases and customer recommendations, the findings in the J.D. Power study are significant. “When overall satisfaction is greater than 900, 75% “definitely will” repurchase the same make again and 95% “definitely will” recommend it. Automakers looking to drive loyalty need to provide a highly satisfying tech usage experience,” the summary concluded. With this in mind alongside self-driving developments, it’s especially important for owners to find value in their driver assistance features if manufacturers hope to win consumer confidence as features progress.
“Consumers are still very concerned about cars being able to drive themselves, and they want more information about these complex systems, as well as more channels to learn how to use them or how and why they kick in,” Kolodge commented on the findings. “If they can’t be sold on lane-keeping—a core technology of self-driving—how are they going to accept fully automated vehicles? …It’s essential that the industry recognize the importance of an owner’s first experience with these lower-level automated technologies because this will help determine the future of adoption of fully automated vehicles.”
Tesla’s Autopilot is perhaps becoming one of the most well-known driver assist features offered by an auto company today, and it’s primarily due to high owner satisfaction. Owners frequently report their positive experiences with the feature’s traffic capabilities, and numerous videos and stories have been shared about how preventative measures taken by Autopilot have prevented serious traffic incidences. What’s more, Tesla’s own safety data validates these owner findings on a macroscale and has led the company to make some functions available even without the Full Self-Driving suite.
In May, Tesla introduced two new active lane monitoring features designed to help prevent drivers from unintentionally leaving their lane of travel named ‘Lane Departure Avoidance’ and ‘Emergency Lane Departure Avoidance.’ They are derived from Autopilot, yet work while it’s not on. The Lane Departure Avoidance applies corrective steering to keep drivers in their intended travel lane if a departure is sensed without a turn signal. Emergency Lane Departure Avoidance is automatically enabled and is designed to return a Tesla vehicle back to its original lane if a departure and an imminent collision are detected, rather than simply alerting drivers of the situation. “As our quarterly safety reports have shown, drivers using Autopilot register fewer accidents per mile than those driving without it,” Tesla’s press release on the lane-oriented features stated.
Lane-keeping technologies may not be big sellers for legacy auto companies, but Tesla is clearly making very good headway with those features.
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.”
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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
