Technical challenges and concepts for Smart LiDAR; safety, reliability and liabilities

About this Session
LiDAR Sensor, which provides redundant environmental information for Level 3 to Level 5 autonomous driving, is the key to ensure safety in autonomous vehicles. The main challenges for automotive-grade LiDAR are closely related to vehicle integration (packaging size, low weight, …), mass production (reliability, productivities, low cost, …), liabilities (Functional safety, laser safety Class1, …). To solve those problems is the shared concern of autonomous driving R&D teams and the core LiDAR manufacturers. Dr. Leilei Shinohara will further analyze major technical challenges for automotive LiDAR especially in terms of improving its safety, reliability, and stability. Through a comparison with the traditional LiDAR system and its limitation, he will introduce a new trend of Smart LiDAR embedded with AI perception algorithms and IC chipset, transforming conventional LiDAR sensors from an information collector to a complete data analysis and comprehension system, outputting structured semantic-level comprehensive environment information in real-time, which greatly improves the safety, reliability, and stability for Level 3 to Level 5 autonomous vehicles.

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