Leveraging a newly released open dataset of Lane Keeping Assist (LKA) systems from production vehicles, this paper presents the first comprehensive empirical analysis of real-world LKA performance. Our study yields three key findings: (i) LKA failures can be systematically categorized into perception, planning, and control errors. We present representative examples of each failure mode through in-depth analysis of LKA-related CAN signals, enabling both justification of the failure mechanisms and diagnosis of when and where each module begins to degrade; (ii) LKA systems tend to follow a fixed lane-centering strategy, often resulting in outward drift that increases linearly with road curvature, whereas human drivers proactively steer slightly inward on similar curved segments; (iii) We provide the first statistical summary and distribution analysis of environmental and road conditions under LKA failures, identifying with statistical significance that faded lane markings, low pavement laneline contrast, and sharp curvature are the most dominant individual factors, along with critical combinations that substantially increase failure likelihood. Building on these insights, we propose a theoretical model that integrates road geometry, speed limits, and LKA steering capability to inform infrastructure design. Additionally, we develop a machine learning-based model to assess roadway readiness for LKA deployment, offering practical tools for safer infrastructure planning, especially in rural areas. This work highlights key limitations of current LKA systems and supports the advancement of safer and more reliable autonomous driving technologies.

Kurt'CyberGuy' Knutsson explores the benefits of AI-powered dashcams for your car. Have you ever wished you had a witness to back you up after a car accident or a road rage incident? Or a way to prevent thieves from breaking into your vehicle? Or a device that could call for help if you were in trouble? Well, now you can have all that and more with the iQ, a new artificially intelligent dashcam from Nextbase.

Consumer Reports has opened a $1 million test track that will be used to evaluate advanced driver assistance systems like Tesla's Autopilot. Consumer Reports test drives around 50 new vehicles annually at its facility in Connecticut each year. And each year, the cars get better at driving themselves … at least a little. Semi-automated advanced driver assistance systems (ADAS), like blind-spot monitors, lane-centering steering and Tesla's Autopilot, are becoming more and more common as cars inch toward full self-driving capability. Now, the organization has built a 1.5-mile track specifically to evaluate the technology.

Tesla (TSLA) will raise the price of its top-end driver assistance system – Full Self-Driving (FSD) – according to a tweet from CEO Elon Musk. Musk said in a tweet on Sunday, "After wide release of FSD Beta 10.69.2, price of FSD will rise to $15k in North America on September 5th." After wide release of FSD Beta 10.69.2, price of FSD will rise to $15k in North America on September 5th. Current price will be honored for orders made before Sept 5th, but delivered later. The cost of the FSD will increase $3,000 on Sept. 5, up from its previous $12,000 price tag.

A'deeply disturbing' video claims to show a Tesla in full self-driving mode running over a child-size mannequin during a test by a safety campaign group. The Dawn Project said the vehicle failed to detect the stationary dummy's presence in the road and hit it over and over again at an average speed of 25mph. It claims that the experiment was carried out under'controlled conditions' on a test track in California. Tesla, which was founded by billionaire entrepreneur Elon Musk, has been approached for a comment by MailOnline but is yet to respond to the video. The US National Highway Traffic Safety Administration (NHTSA) confirmed that it'currently has an open and active investigation of Tesla's Autopilot active driver assistance system'.

Advanced driver assistance systems (ADAS) are designed to improve vehicle safety. However, it is difficult to achieve such benefits without understanding the causes and limitations of the current ADAS and their possible solutions. This study 1) investigated the limitations and solutions of ADAS through a literature review, 2) identified the causes and effects of ADAS through consumer complaints using natural language processing models, and 3) compared the major differences between the two. These two lines of research identified similar categories of ADAS causes, including human factors, environmental factors, and vehicle factors. However, academic research focused more on human factors of ADAS issues and proposed advanced algorithms to mitigate such issues while drivers complained more of vehicle factors of ADAS failures, which led to associated top consequences. The findings from these two sources tend to complement each other and provide important implications for the improvement of ADAS in the future.

Fully autonomous vehicles are already operating on city streets, but a study published last year in AI and Ethics reported that 74% of survey respondents said they do not trust AVs nor believe AVs can perform better than a normal driver. However, a number of companies are developing technologies to enhance safety for and around autonomous vehicles in urban areas. According to Statista, 58 million autonomous vehicles are projected to be sold globally in 2030. Cities need to be ready for them. "The nation's city leaders see that AV technology is here so it cannot be ignored or left in a regulatory limbo while it operates on our streets," said Houston city council member and Vice Mayor Pro Tem Martha Castex-Tatum in testimony to the U.S. House of Representatives Committee on Transportation and Infrastructure earlier this year.

Nearly 150,000 Tesla cars are using the company's new "safety score," a tool rolled out last month to determine whether owners can access the beta version of its "Full Self-Driving" software, executives said during its third quarter earnings call. While 150,000 cars are now part of the Full-Self Driving (FSD) beta enrollment program, a fraction of drivers have been given access to the software. Only 2,000 drivers have been able to test the FSD program over the past year. Earlier this month, Tesla rolled out version 10.2 to around 1,000 additional owners with perfect safety scores. Tesla charges $10,000 for the FSD software, which CEO Elon Musk has promised for years will one day deliver full autonomous driving capabilities.

The US highway safety watchdog asked 12 automakers Tuesday to provide data on their driver assistance systems as part of a preliminary investigation of Tesla, whose cars were involved in several accidents with first responder vehicles. The National Highway Traffic and Safety Administration seeks to conduct a benchmark analysis of vehicles whose models have the ability, under certain circumstances, to automatically control both the steering and the breaking or acceleration. NHTSA sent letters, dated September 13 and seen by AFP, to BMW, Ford, General Motors, Honda, Hyundai, Kia, Mercedes-Benz, Nissan, Stellantis, Subaru, Toyota and Volkswagen. The agency began its probe in August after documenting 11 Tesla accidents since early 2018 involving a car from the company founded by tech titan Elon Musk and emergency vehicles including police cruisers. The incidents included one fatal crash and seven that resulted in injuries to a total of 17 people, according to the NHTSA.

Tesla's Autopilot may have prevented a deadly crash when the technology brought a Model S to stop after detecting the driver, who was intoxicated, was no longer responsive. The incident occurred on a highway in Norway on Friday, when a 24-year-old man got behind the wheel after a night of drinking and fell asleep while the vehicle was still in motion. The Autopilot system was activated during the trip, which kept the car in its lane and away from other vehicles on the road. The Eastern Police District released a statement on its Twitter account saying the man was drunk and denied driving'although there is video of him in the car.' Tesla's Autopilot may have prevented a deadly crash when the technology brought a Model S to stop after detecting the driver, who was intoxicated, was no longer responsive Tesla's Autopilot is an advanced driver assistance system that matches the speed of the Tesla with surrounding traffic, keeps the vehicle in its lane and guides the car through lane changes and ramps. The technology also automatically engages the turn signal and takes the correct exit – all of these functions may have saved the life of the Norwegian man and those in surrounding vehicles. The video of the intoxicated driver, who's identity has yet to be revealed, was published on Twitter, which shows him in the front seat of a white Model S driving down the highway and toward the Nøstvet tunnel, according to Electrek.