Advanced driver assistance systems (ADAS) is the fastest growing technology segment in the automotive market, worth an estimated $21 billion in 2020 and predicted to reach nearly $32 billion by 2023 according to Statista.

ADAS capabilities – such as lane departure warning, blind spot detection and emergency braking – have achieved widespread market penetration, significantly increasing driver safety and improving the driving experience. Meanwhile, more advanced semi-autonomous technologies are paving the way for self-driving vehicles in the future.

Artificial Intelligence (AI) is one of the most critical components in ADAS, vastly outperforming traditional software techniques in real-time perception, prediction and decision-making tasks. As future ADAS systems tackle more complex self-driving scenarios, even more AI content will be required. However, the current approach to semi-autonomous architecture makes it prohibitively expensive for vehicles in the mid-range to adopt.

In this whitepaper, we examine the commercial and technological challenges to wider adoption of ADAS and set out our roadmap to deliver semi-autonomous features into the mid-range vehicle segment.

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