Advanced driver assistance systems (ADAS) is the fastest growing technology segment in the automotive market and paving the way for self-driving vehicles. AI is one of the most critical components in ADAS, vastly outperforming traditional software techniques in real-time perception, prediction and decision-making.
As future ADAS tackle more complex scenarios, more advanced AI will be required. However, the current approach to semi-autonomous ADAS architecture makes it prohibitively expensive for vehicles in the mid-range to adopt.
In this webinar we shared in-depth insights from our recent commercial work in this area and explored:
- The commercial and technological challenges to wider ADAS adoption
- How recent advances in deep learning are radically enhancing ADAS
- Emerging techniques in ultra-low power and ultra-low cost compute at the edge
- Strategies to deliver semi-autonomous ADAS into the mid-range vehicle segment
- Oli Qirko, Head of Industrial, Consumer & Energy, Cambridge Consultants
- Thomas Carmody, Head of Transport and Infrastructure, Cambridge Consultants