About the Course

This course is to prepare learners to become a professional in autonomous driving vehicles..

Main Contents

Introduction to Autonomous Driving  
  • How a self-driving car works
  • Vehicle Levels of automation
Computer Vision for Self-Driving Cars  
  • Perception tasks
  • Object detection
  • Segmentation
  • Pose estimation
  • 3D point clouds and 3D perception
Sensing in Self-Driving Cars 
  • Radar
  • LiDAR and 3D LiDAR perception
  • Camera and 2D camera data
  • Sensor Fusion
Localization  
  • Overview
  • Simultaneous Localization and Mapping (SLAM)
  • Improvements to basic SLAM
Planning  
  • Autonomous vehicle planning systems
  • Mission planning
  • Behavioral planning
  • Motion planning
Control  
  • Classical control
  • Model predictive control
  • Trajectory generation and tracking
Driver State  
  • Driver state detection
  • Driver glance region classification
  • Driver pose estimation
  • Driver emotion
VoxelNet for Self-Driving Cars
  • Architecture
  • Feature learning network
  • Region proposal network
  • Average precision
  • Model training
Complex YOLO for Self-Driving Cars  
  • Architecture
  • Average precision
  • Model training
FaF for Self-Driving Cars  
  • Architecture
  • Average precision
  • Model training
LidCamNet for Self-Driving Cars  
  • Architecture
  • Average precision
  • Model training