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Steven J. Vaughan-Nichols, aka sjvn, has been writing about technology and the business of technology since CP/M-80 was the cutting edge, PC operating system; 300bps was a fast Internet connection; WordStar was the state of the art word processor; and we liked it. Linux has long played a role in cars. Some companies, such as Tesla, run their own homebrew Linux distros. Audi, Mercedes-Benz, Hyundai, and Toyota all rely on Automotive Grade Linux (AGL). AGL is a collaborative cross-industry effort developing an open platform for connected cars with over 140 members.
Self-driving car market race heats up; S. Korean regulations lag behind: report (Yonhap) South Korea is lagging behind in revising regulations to prepare for the commercialization of autonomous vehicles compared to other major countries such as the US, Germany and Japan, a Seoul-based think tank said Sunday. The market size of autonomous, or self-driving, vehicles is expected to grow from $7.1 billion in 2020 to $1 trillion by 2035, a report by the Korea Economic Research Institute showed. More than half of the newly launched cars to be sold in 2030 are expected to be equipped with level three autonomous driving technology. Level three autonomous driving means that the driver can hand over control to the vehicle, but must be ready to take over when prompted in a limited number of areas such as on the freeway. Autonomy in vehicles is often categorized in six levels from level zero to five according to a system developed by the US-based SAE International.
Note: This article was originally published as an essay for an ethics class. I have decided to keep it in the same format given the sources used. It was originally written sometime in 2015. Quite interesting to observe similarities, differences, and growth in just the short span of 3 years when it comes to driverless cars and autonomous technology. Thousands of years ago, humans roamed the earth on nothing but bare feet. Hundreds of years ago, we rode horses and carriages, even trains. Then, Henry Ford and the automobile came along to pave the way for one of today's most common ways of transportation.
Lucid Motors will use Nvidia's auto-grade computer chips in its vehicles to enable advanced driver assistance and autonomous driving features, the companies announced Tuesday. The automaker's current and future lineup will be built on Nvidia's end-to-end Drive Hyperion platform. Hyperion is the latest iteration of Nvidia's Drive platform that allows automakers to customize their own driving features. This new hardware will form the basis for a new suite of driving features, including advanced driver-assistance systems (ADAS), automated parking, and autonomous driving, the companies said. Lucid released its first EV, the Lucid Air, last year and is already working on a follow-up: a long-range electric SUV code-named Project Gravity.
Over the past decade, technology and automotive pundits have predicted the "imminent" arrival of fully autonomous vehicles that can drive on public roads without any active monitoring or input from a human driver. Elon Musk has predicted his company Tesla would deliver fully autonomous vehicles by the end of 2021, but he made similar predictions in 2020, 2019, and 2017. Each prediction has fallen flat, largely due to real-world safety concerns, particularly related to how self-driving cars perform in adverse conditions or situations. Despite such proclamations from Tesla, which released its optimistically named Full Self Driving capability for AutoPilot in October 2021, fully automated self-driving cars have not yet arrived. Instead, most manufacturers are offering systems that feature capabilities that generally fall within the first three of the six levels of autonomy defined by the Society of Automotive Engineering (SAE), which range from Level 0 (no driving automation) to Level 5 (full self-driving capabilities under all conditions).
Jaguar Land Rover is teaming up with Nvidia to install high-powered computers in its vehicles to enable advanced driver assistance and autonomous driving features. Starting in 2025, all JLR vehicles will come with Nvidia's end-to-end Drive Hyperion platform installed, the companies said. Hyperion is the latest iteration of Nvidia's Drive platform that allows automakers to customize their own driving features. This new hardware will form the basis for a new suite of driving features, including advanced driver assistance systems, automated parking, and autonomous driving, the companies said. "Orin is the AI brain of the car, and Drive Hyperion is the central nervous system," said Danny Shapiro, Nvidia's vice president for automotive.
Artificial intelligence (AI) features are increasingly being embedded in cars and are central to the operation of self-driving cars (SDC). There is little or no effort expended towards understanding and assessing the broad legal and regulatory impact of the decisions made by AI in cars. A comprehensive literature review was conducted to determine the perceived barriers, benefits and facilitating factors of SDC in order to help us understand the suitability and limitations of existing and proposed law and regulation. (1) existing and proposed laws are largely based on claimed benefits of SDV that are still mostly speculative and untested; (2) while publicly presented as issues of assigning blame and identifying who pays where the SDC is involved in an accident, the barriers broadly intersect with almost every area of society, laws and regulations; and (3) new law and regulation are most frequently identified as the primary factor for enabling SDC. Research on assessing the impact of AI in SDC needs to be broadened beyond negligence and liability to encompass barriers, benefits and facilitating factors identified in this paper. Results of this paper are significant in that they point to the need for deeper comprehension of the broad impact of all existing law and regulations on the introduction of SDC technology, with a focus on identifying only those areas truly requiring ongoing legislative attention.
When we talk about autonomous driving today, we typically mean cars that can drive by themselves on the highway, recognize some of the dangers on the road, and perhaps do a few advanced tasks such as autonomously change lanes or park themselves. But advanced stunts like drifting are still firmly in the realm of human driving...or are they? Toyota Research Institute has released a video showing a modified Toyota Supra autonomously drifting around obstacles on a closed track, which it says is a world first. The driving's impressive – with no prior knowledge of who's driving, I couldn't tell that it was the car itself, with the driver keeping his hands off the wheel throughout the stunt. The goal of the stunt, Toyota claims, isn't to create cars that can win drifting competitions, but to make autonomous driving systems that can react in situations where human drivers can't. "Through this project, we are expanding the region in which a car is controllable, with the goal of giving regular drivers the instinctual reflexes of a professional race car driver to be able to handle the most challenging emergencies and keep people safer on the road," Avinash Balachandran, senior manager of TRI's Human Centric Driving Research, said in a statement.
Autonomous vehicles are on the horizon and will be transforming transportation safety and comfort. These vehicles will be connected to various external systems and utilize advanced embedded systems to perceive their environment and make intelligent decisions. However, this increased connectivity makes these vehicles vulnerable to various cyber-attacks that can have catastrophic effects. Attacks on automotive systems are already on the rise in today's vehicles and are expected to become more commonplace in future autonomous vehicles. Thus, there is a need to strengthen cybersecurity in future autonomous vehicles. In this article, we discuss major automotive cyber-attacks over the past decade and present state-of-the-art solutions that leverage artificial intelligence (AI). We propose a roadmap towards building secure autonomous vehicles and highlight key open challenges that need to be addressed.
As a tech analyst, one of the particularly exciting topics I get to cover is the march towards fully autonomous vehicles. I've long projected that these next generation vehicles, ranging from semi-to-fully autonomous, will be one of the most impactful developments we see in our lifetimes. As with many nascent technologies, it's looking like some of the earliest applications will be in the commercial sector. Trucking, specifically, stands to benefit from new levels of autonomy, promising gains in efficiency, safety, comfort and sustainability. For several years now, I've been closely watching Plus (formerly known as Plus.ai), a pioneer in self-driving truck technology.