Key challenges for the future of advanced driver assistance systems (ADAS)

Advanced driver assistance systems (ADAS) is the fastest growing technology segment in the automotive market, worth an estimated $24 billion in 2018 and predicted to reach $92 billion by 2025.

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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Author
Oli Qirko
President, North America, Cambridge Consultants

Oli has 20 years’ experience of helping leading global corporations to develop breakthrough products and services in a range of markets – from consumer and industrial to logistics and transportation. At Cambridge Consultants, she now partners with Fortune 100 and start-up companies to launch digital transformation and automation initiatives. These leverage global organization capabilities in AI, advanced sensing, robotics and wireless communication. Oli holds a master’s in electrical engineering from WPI and an MBA from MIT. As well as serving on the WPI Engineering Advisory Board, Oli lectures at MIT Sloan School of Management. There, she mentors CXOs and executives on how to manage the most critical and complex organizational challenges in business, technology and global operations.

 

 

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