Next-generation radar, enhanced by AI and advanced signal processing, is emerging as an important enabler of autonomous driving, offering long-range detection, precise velocity measurement, and robust all-weather performance in real-world conditions.
In this technology insight, leading experts explore the critical questions surrounding automotive radar, offering a multi-perspective analysis of its current capabilities, the key barriers to higher-performance deployment, and how its role may evolve on the path to Level 4+ autonomy.
Contributing experts:
- Dr Yanni Zhou, Patent & Technology Analyst, KnowMade | LinkedIn
- Markus Baum, Senior Partner, Roland Berger | LinkedIn
- Charlie Pope, Principal, Roland Berger | LinkedIn
Key questions explored:
- How mature is automotive radar technology today, and how effectively is it fulfilling its role alongside cameras and LiDAR in current ADAS and self-driving systems?
- Of the key technical and integration barriers limiting radar’s performance in higher-level autonomy – from angular resolution and object classification to interference management and sensor-fusion complexity – which are the most critical to overcome first?
- Which advances in radar design, signal processing, and AI-enabled perception show the most promise for closing these gaps, and how close are they to production-ready performance?
- As perception requirements grow more demanding, is radar’s role in the autonomous sensor stack expanding beyond its traditional strengths, and could next-generation radar take on functions currently assigned to cameras or LiDAR?
- Looking out ten years, what role will radar ultimately play in achieving scalable Level 4+ autonomy, and will it remain a complementary sensor, or become a central pillar of the perception stack?