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
Thomas Carmody
Head of Transport & Infrastructure

Thomas works with automotive manufacturers and technology providers to develop transformative products and services, leveraging the company’s unique combination of world-leading expertise in silicon, sensing, connectivity, AI. 

 

With over 16 years’ experience in the automotive market, Thomas has led the global development of breakthrough automotive technologies. This includes the world’s first fully AEC-Q100 qualified Bluetooth, BLE and Wi-Fi semiconductor devices, which Thomas brought to market in his previous role as Head of Automotive Connectivity at CSR - later acquired by Qualcomm.  

 

Contact Thomas on LinkedIn or email