Autonomous vehicles are one of the most complex challenges for Artificial Intelligence today, and bringing AVs to market requires the sharing of tremendous knowledge and expertise in end-to-end solutions. For those who do not know, NVIDIA is primarily recognized for providing graphics cards (GPUs) for computers and games, but in recent years thanks to the improvement of high processing hardware, the company has become an essential partner of the automobile industry in the development of artificial intelligence, a fundamental part in the development of autonomous vehicles. After all, this new generation of autonomous vehicles requires enormous computational power and it means that as important as talking about the engine or the vehicles's transmission, with Autonomous Vehicles it will be fundamental to talk about its hardware and software. That's why is at the data center, where autonomous vehicles are born and raised. It is where the car's Deep Neural Networks (DNNs) learn how to detect objects and perceive their surroundings and where self-driving software can be tested and validated over millions of virtual miles.
This ebook, based on the latest ZDNet / TechRepublic special feature, examines how 5G connectivity will underpin the next generation of IoT devices. Autonomous cars (and other vehicles, such as trucks) may still be years away from widespread deployment, but connected cars are very much with us. The modern automobile is fast becoming a sensor-laden mobile Internet of Things device, with considerable on-board computing power and communication systems devoted to three broad areas: vehicle location, driver behaviour, engine diagnostics and vehicle activity (telematics); the surrounding environment (vehicle-to-everything or V2X communication); and the vehicle's occupants (infotainment). All of these systems use cellular -- and increasingly 5G -- technology, among others. Although 5G networks are still a work in progress for mobile operators, the pace of deployment and launches is picking up.
When most people think of autonomous vehicles, an image of a fully self-sufficient vehicle that can drive all on its own often comes to mind. However, not all autonomous vehicles can drive without any human intervention. In reality, there are several different levels of autonomous vehicles that vary based on how much driver assistance they provide. Below, we will walk you through the six different levels of autonomous vehicles. A vehicle that has an automation level of zero essentially does not have any autonomous capabilities.
Declaring "it's no longer a question of if...but when" autonomous vehicles are used in retail, President and CEO of Walmart (NYSE:WMT) U.S. John Furner announced the retail titan's intention to invest in General Motors' (NYSE:GM) Cruise self-driving car company in a press release today. Furner said the move will "aid our work toward developing a last mile delivery ecosystem that's fast, low-cost and scalable." The Walmart investment brings the total of Cruise's most recent funding round to $2.75 billion, though neither GM nor Cruise provides specifics on how much each individual company contributes to the whole, CNBC reports. Other investors in the subsidiary include GM itself, Microsoft, Honda Motor, and institutional investors. Among other projects, Cruise intends to roll out self-driving taxis in Dubai within the next two years.
Walmart is signaling its commitment to autonomous deliveries with a new investment in self-driving company Cruise. The two already have a cozy relationship, having recently worked together on a delivery pilot in Scottsdale, Arizona. Walmart was so impressed with Cruise's "differentiated business, unique tech and unmatched driverless testing" that it decided to take part in the GM subsidiary's $2.75 billion funding round. The investment will see Cruise become an important part of the retailer's "last mile delivery ecosystem" -- industry parlance for the final journey from warehouse to customer. Walmart has struck additional partnerships on driverless deliveries with companies including Google's Waymo, Ford and Udelv.
Losses to the tune of billions are experienced due to the rise of cyber-attacks in the automotive industry, and they are becoming progressively worse as more auto manufacturers join the autonomy space. Industry experts argue that autonomy is the future of the automotive industry, mainly because driverless cars are safer, more comfortable, and more convenient than regular cars. However, there is a downside to this technology: susceptibility to cyber-attacks. Attacks range from physical to long-range digital attacks. As we know, a new cyber-attack vector is born every time new development occurs in the tech space.
While automakers and investors alike are placing big bets on autonomous vehicles, a remaining requirement for full-integration of AVs lies in automated technologies being able to operate in poorly-marked road surfaces, off-road terrain, and in inclement weather. By overcoming these last common obstacles encountered by traditional lidar and camera-based sensors, the industry will reach a critical step in the further development of ADAS and AVs that are both safe and reliable. A technology called Ground Positioning Radar has shown incredible promise when it comes to reaching that final step. A company called WaveSense, is currently the world's only provider of GPR for precise localization of autonomous and highly-automated vehicles, and the company recently announced a funding round of $15 million. WaveSense has become an integral company within the ADAS industry, having been awarded in 2019 the top autonomous driving project and best-in-show at the North American International Auto Show and last year appointed former Ford President, Joe Hinrichs, to the Board of Directors.
Researchers from the Queensland University of Technology (QUT) have touted the use of artificial intelligence to determine the feasibility of autonomous cars on Australian roads. The QUT Centre for Robotics has conducted research projects into mapping for autonomous cars using AI. The centre's acting director Professor Michael Milford said map updating is a major challenge for autonomous vehicle adoption. Milford said given mapping isn't a globally mature field, there are opportunities for Australia to catch up quickly. "Current out-of-the-box European mapping solutions don't recognise unique Australian signs or infrastructure and require customisation," he said.
Waymo is a self-driving car company, but they don't particularly like using that terminology. Instead they prefer fully autonomous as a more accurate way to describe driverless or autonomous driving technology. What consumers may not fully understand is the difference between self-driving and fully autonomous. A self-driving car is a type of vehicle that can provide some level of automation like ADAS (Advanced Driver Assistance System) or automatic cruise control. It still requires driver attention for proper operation or it can lead to accidents.
A team of researchers in Germany have come up with a safety system that could warn drivers of autonomous cars that they will have to take control up to seven seconds in advance. A team of researchers at the Technical University of Munich (TUM) has developed a new early warning system for autonomous vehicles that uses artificial intelligence to learn from thousands of real traffic situations. The study of the system was carried out in cooperation with the BMW Group. Researchers behind the study claim that if used in today's self-driving vehicles, it could offer seven seconds advanced warning against potentially critical situations that the cars cannot handle alone – with over 85 per cent accuracy. To make self-driving cars safe in the future, development efforts often rely on sophisticated models aimed at giving cars the ability to analyse the behaviour of other traffic.