Autonomous Vehicles: The Rise of AI

Autonomous Vehicles: The Rise of AI

Few technical advances have been as disruptive as AI. It's a technological advancement that will soon be accountable for driving our cars for us. This month's four blog postings will focus on the rise of autonomous vehicles.
Autonomous vehicles (AV) have been dominating headlines and tech talks for a few years now. Autonomous vehicles are now largely seen as the automotive industry's future, posing the greatest upheaval to transportation and logistics since the automobile's creation. But what are autonomous vehicles, and how does AI help develop them?

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Understanding driving automation levels

Autonomous car is commonly confused with driverless or self-driving vehicle, however the reality is far more complex.

SAE International produced a global standard for vehicle automation, specifying five levels of autonomy. Truly autonomous levels 3–5 are powered by AI models built on image, sensor, satellite, and video data.

Level 1 – Systems that help the driver but do not take full control. A parking sensor and lane centering are already typical in higher-end vehicles. Hands-on operation means AI has no role in level-1 automation because the machine cannot make decisions on its own.

Level 2 – These vehicles may offer hands-free acceleration, steering, self-parking, and braking. Because the car cannot make decisions on its own, the driver must constantly watch the functioning and be ready to act. This level does not require AI technology. Rather, the driver must still watch and react to the environment.

It can navigate automatically, sync with traffic signals, and urge the driver to intervene if specific circumstances aren't satisfied. One example is the Audi A8's self-driving traffic jam chauffeur system.

Level 4 — Fully autonomous cars that use advanced adaptive AI models powered by active learning and substantial training. But first, certain conditions must be met. Then they could only be totally autonomous on highways. A popular example is a driverless cab.

Level 5 — The maximum level of automation is similar to level 4, but with the capacity to drive in all conditions. A steering wheel and pedals are optional, as is human intervention. In all situations, the vehicle totally replaces the human driver. We're still a long way off, but technology is rapidly evolving.

Currently, most entry-level vehicles lack any self-driving technology and are classified as level 0 by the SAE. Level-1 is already common in high-end vehicles, while level-2 is slowly approaching the market.

True autonomy (levels 3–5) is still in its infancy. For example, Audi's autonomous traffic jam navigation was set to premiere in Europe, but it has been delayed due to regulatory issues.

AV Innovators Spotlight

The influence of driverless automobiles will be broad, not only in public transportation. Smaller-scale applications range from autonomous golf carts to zero-touch pizza delivery.

Artificial intelligence and related technologies are advancing to the point where society will soon begin to reap the benefits of autonomous automobiles. Better road safety, efficiency and even lower emissions. It may take time, but progress is being made.

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Driver Technologies developed a free smartphone app that delivers AI-assisted navigation and accident avoidance for drivers worldwide. They wanted all drivers in the world to have access to driver safety tools. Also coming soon: DriverCloud, a comprehensive collection of anonymised (and CloudFactory annotated) highway data for automakers, instructors, and AV startups.

Greater Exposure — Palo Alto Luminar focuses on autonomous vehicle guidance. They built a 250m LiDAR sensor, considerably raising the bar for safety in driverless vehicles. Find out how our managed workforce helped Luminar innovate.

Embark produces self-driving trucks and now transports freight across the Southwest. Embark has driven across the country, in rain and fog, and between transfer points. Testing level 4 autonomous trucks now. Here's a look into an Embark truck driver's day.

Companies in the AI sector are under increasing pressure to create, test, and commercialise solutions that will make automated transportation safer and more reliable. After all, road safety leaves no space for error. That's why extensive item labelling in photos and videos is required to train the computer vision model to appropriately perceive the world.

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CloudFactory's picture annotation technology prepares huge amounts of data needed to effectively train AI systems. Learn how we're making autonomous vehicles safer.