Autonomous cars are indispensable when humans go further down the hands-free route. Although existing literature highlights that the acceptance of the autonomous car will increase if it drives in a human-like manner, sparse research offers the naturalistic experience from a passenger's seat perspective to examine the humanness of current autonomous cars. The present study tested whether the AI driver could create a human-like ride experience for passengers based on 69 participants' feedback in a real-road scenario. We designed a ride experience-based version of the non-verbal Turing test for automated driving. Participants rode in autonomous cars (driven by either human or AI drivers) as a passenger and judged whether the driver was human or AI. The AI driver failed to pass our test because passengers detected the AI driver above chance. In contrast, when the human driver drove the car, the passengers' judgement was around chance. We further investigated how human passengers ascribe humanness in our test. Based on Lewin's field theory, we advanced a computational model combining signal detection theory with pre-trained language models to predict passengers' humanness rating behaviour. We employed affective transition between pre-study baseline emotions and corresponding post-stage emotions as the signal strength of our model. Results showed that the passengers' ascription of humanness would increase with the greater affective transition. Our study suggested an important role of affective transition in passengers' ascription of humanness, which might become a future direction for autonomous driving.

The problem is that for an AI to learn to handle the chaos of real roads, it has to be exposed to the full range of events that it might encounter. That's why driverless-car firms have spent the last decade driving millions of miles on streets around the world. A few, like Cruise and Waymo, have begun testing vehicles without human drivers in a handful of quiet urban environments in the US. But progress is still slow. "Why haven't we seen an expansion of these small pilots? Why aren't those vehicles everywhere?" asks Urtasun.

An artificial intelligence has beaten four of the world's best human drivers on three different tracks in the racing video game Gran Turismo Sport, by gaining ground at the most difficult parts of a track. The AI, named GT Sophy, was able to execute tactical moves such as using an opponent's slipstream to boost itself forwards and block its opponents from passing. Peter Wurman at Sony AI in New York and his colleagues trained the system using deep reinforcement learning, a type of machine learning that uses rewards and penalties to teach the AI's neural network how to win. During training, GT Sophy, which was running on a separate computer, played the game on up to 20 PlayStation 4 consoles simultaneously. The team gave the AI the ability to accelerate, brake and steer, along with real-time information on the position of the cars in the game, including its own, and a map of the next 6 seconds of the track, which meant sight of a longer distance ahead when the AI travelled faster.

The advancements in artificial intelligence, IoT, computer vision, and other advanced technologies are driving automation in multiple industries across the world. But there has been a concern regarding the replacement of human employees for AI smart functionalities. Thus, it has also affected the automobile industry, especially the community of human truck drivers. There have been some improvements from multiple self-driving truck companies that are launching autonomous trucks. Let's explore who will win the on-road race-- AI drivers or human truck drivers in 2022 and beyond.

Baidu's autonomous vehicle platform, Apollo, gets an upgrade. The Chinese IT firm, which started out ... [ ] as a Google imitator, is now going toe-to-toe with Google subsidiary Waymo, as well as Samsung and Intel. Baidu wants to one up Google on its AI powered car platform called Apollo. They might pull just pull it off. In any event, they at least have to be considered in the same league.

Car manufacturers know: There's a huge amount of interest in AI-driven cars. Many people would love to automate the task of driving, because they find it tedious or at times impossible. A competent AI driver would have lightning-fast reflexes, would never weave or drift in its lane, and would never drive aggressively. An AI driver would never get tired and could take the wheel for endless hours while we humans nap or party. While AI does need huge volumes of data to program and guide it, that shouldn't be a problem.

Ever since we first heard about this company called Roborace that builds driverless AI racing cars, we knew we had to see it in action at some point -- change was in the air. A few weeks ago, we finally had the opportunity to do so and joined the final track test for Roborace's Season Alpha. Roborace is an autonomous-vehicle racing series that combines fully-electric race cars with artificial intelligence, the first series of its kind in the world. Roborace was established to "accelerate the development of autonomous software by pushing the technology to its limits in a range of controlled environments." In 2018, one of Roborace's driverless vehicles, the RoboCar, completed the first-ever autonomous hill climb at Goodwood Festival of Speed.

The racing industry is on the fast track to driverless racecars, thanks to AI. At the center of this evolution is Roborace, the world's first autonomous racing competition. Conceived by renowned car designer Daniel Simon -- a former Bugatti designer who's gone on to create various cars for Hollywood -- the "Robocar" is designed, developed, and built by the Roborace organization. Teams compete by writing the software and developing deep neural networks that consume the sensor data to see, think, and act. The cars -- which are 4.8-meters-long -- can reach speeds of over 300 kilometers per hour.

Product shipments of artificial intelligence (AI) systems for vehicles will grow from 7 million in 2015 to 122 million by 2025, which, according to IHS Technology, is a reflection of the automotive industry's growing appetite for AI.