Self-Driving Cars

The Steps to Making Self-Driving a Reality

This article is based in part on a story that originally appeared in It Is Innovation (i3) magazine, published by the Consumer Technology Association (CTA)®.

Overview Despite previous forecasts, self-driving vehicles have yet to become mainstream. Industry experts point out that there are still things to smooth out on the road toward consumer use of self-driving cars.

As the automotive industry continues on the path toward making consumer-ready self-driving vehicles a reality, it has also had to address risks that have made the process harder than anticipated.

On the top of the list of concerns is safety. With self-driving cars still running into obstacles while semi-autonomous, there remain challenges to overcome for consumers to believe a self-driving vehicle is ready for the road.

“What we’re trying to ensure is that we achieve the highest level of safety that we possibly can,” said Danny Shapiro, senior director of automotive at NVIDIA Corp., in i3 magazine.

Experts in the vehicle tech space still see self-driving vehicles becoming conventional in the coming years, however, and see concrete ways to get the industry where it needs to be.


Define and Understand

Shared definitions and standards will enable all stakeholders in the vehicle tech space, from developers to regulators, to describe potential scenarios and share metrics without confusion.

“The industry suffers from ambiguity in terminology,” said Heikki Laine, vice president of product and marketing at Cognata Ltd.

Foretellix developed a “measurable scenario description language” and is contributing to the development of a new standard to regulate and define safety measures for self-driving vehicles.


Test and Trial

Cognata’s simulation platform aims to accelerate the movement of self-driving systems to market. By providing training data with realistic 3D environments, Cognata enables automakers and suppliers to test and analyze developments across a variety of realistic scenarios.

Cartica AI, along the same lines, developed an automotive visual intelligence platform that teaches vehicles to see the world through object signatures. The car will learn and improve through experience, ultimately curating a robust safety system.

Testing, for both humans and the vehicles themselves, will allow developers to identify and address potential problems in early stages.


Refine and Roll Out

The application of autonomous tech in other industries, such as agriculture or mining, can also provide a simpler environment in which to test, analyze and refine the technologies and strategies before they are transferred to self-driving cars.

In the next five years, automakers will create and release in-vehicle platforms that can improve a vehicle’s artificial intelligence and be updated frequently, allowing self-driving cars to be truly autonomous and evolving.

As companies develop software and understand data for self-driving vehicles, sharing learnings across the industry can shift the vehicle tech space toward making fully autonomous cars a reality.

Learn more about some of the challenges for self-driving cars in i3 magazine.


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