Date: Tuesday, May 17 (Main Conference Day 1)
Start Time: 2:05 pm
End Time: 2:35 pm
Enabling safe, comfortable and affordable autonomous driving requires solving some of the most demanding and challenging technological problems. From centimeter-level localization to multimodal sensor perception, sensor fusion, behavior prediction, maneuver planning and trajectory planning and control, each one of these functions introduces its own unique challenges that must be solved, verified, tested and deployed on the road. In this talk, we will review recent trends in AI workloads for autonomous driving as well as promising future directions. We will cover AI workloads in camera, radar and lidar perception, AI workloads in environmental modeling, behavior prediction and drive policy. To enable optimized network performance at the edge, quantization and neural architecture optimization are typically performed either during training or post-training. We will cover the importance of hardware-aware quantization and network architecture optimization, and introduce the innovation done by Qualcomm in these areas.
