Auto Industry and Tech Convergence Propel 69.3% of New Vehicles to Level 2++ Automation by 2030

The automotive industry, in conjunction with major suppliers in Artificial Intelligence (AI), high-performance compute, mapping, and location intelligence, is investing heavily in the development and deployment of assisted and autonomous driving. According to global technology intelligence firm ABI Research, in 2030, 69.3% of all new passenger vehicle sales will have an SAE driving automation level of 2+ or higher. In its latest whitepaper, A Scalable Approach to ADAS and Autonomous Driving, ABI Research explains the broad spectrum of applications that will support drivers to drive more safely, take on specific tasks on the driver’s behalf, or ultimately entirely replace drivers through the automation of the entire driving process.

“Different autonomous applications vary in features and the level of driver involvement. Some demand constant supervision, while others permit manual, visual, or cognitive disengagement. Active safety systems offer limited support, keeping the driver fully in control. In contrast, driverless vehicles eliminate the need for human operators by handling all driving tasks autonomously,” says James Hodgson, Smart Mobility and Automotive Research Director at ABI Research. “Therefore, the automotive industry should adopt a scalable approach to their active safety, semi-autonomous, and fully driverless applications. Maximizing the re-use of components between different feature/disengagement combinations will yield many benefits to the market.”

The whitepaper, A Scalable Approach to ADAS and Autonomous Driving, provides an overview of each SAE Level and explores the technology implications of ADAS and active safety, 360-degree perception, high-performance compute, and the redundancy in perception, processing, and software. It also discusses the core role of safety rating agencies in making cars safer and driving the adoption of active safety.

“Overall, the only feasible approach to delivering on feature-rich and unsupervised automation is to construct today’s supervised autonomous applications on an architecture that has the potential to scale by adding technologies that will replace the supervisory role that human drivers play today,” Hodgson concludes. 

For more information, download the whitepaper, A Scalable Approach to ADAS and Autonomous Driving.  The whitepaper is also available in Chinese and Japanese.