Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

RWTH Aachen University

Automated and Connected Driving Challenges

RWTH Aachen University via edX

Overview

Automated and connected driving is a major topic in automotive research and industry at the moment. The MOOC "Automated and Connected Driving Challenges (ACDC)" introduces participants to some of the latest research challenges and provides the possibility to develop and test automated and connected driving functions step by step.

This course first provides a comprehensive introduction to the Robot Operating System (ROS), which is a popular software framework for automated vehicle prototypes. On this basis, participants then learn how to develop and integrate modules for sensor data processing, object fusion & tracking, vehicle guidance, and connected driving. In particular, this MOOC allows participants to

  • develop functions for automated and connected vehicles using Python and C++;
  • integrate their developed functions into the Robot Operating System (ROS);
  • train neural networks for environment perception tasks using TensorFlow;
  • learn how to use tools like: Linux, Terminal, Docker, ROS, RVIZ, Juypter Notebooks, Git.

At the end of the course, you may optionally choose from a provided list of open research challenges and start working on your own contribution to automated and connected driving.

Syllabus

Week 1-3: Introduction & Tools

  • Introduction to current challenges in automated and connected driving
  • Introduction to the course tools and setup
  • Introduction to the Robot Operating System (ROS1 & ROS2 Outlook)

Week 4-7: Sensor Data Processing

  • Introduction to Sensor Data Processing
  • Semantic Camera Image Segmentation
  • Semantic Point Cloud Segmentation
  • Object Detection in Point Clouds
  • Occupancy Grid Mapping using Point Clouds
  • Camera-based Semantic Grid Mapping

Week 8-9: Object Fusion and Tracking

  • Introduction to Object Fusion and Tracking
  • Object Prediction
  • Object Association
  • Object Fusion

Week 10: Winter Break

Week 11-12: Vehicle Guidance

  • Introduction to Vehicle Guidance
  • Navigation-Level
  • Guidance-Level
  • Stabilization-Level

Week 13-14: Connected Driving

  • Introduction to Connected Driving
  • Collective Cloud Functions
  • V2I-Communication

Week 13-16: Final Exam Period

  • Exam can be taken anywhere in this period

(Optional) Week 14+

  • Self-paced work on an automated and connected driving challenge you may choose
  • List of challenges, instructions, data, supporting materials are provided
  • Challenges can be tackled alone or in groups
  • Your results may be published on your personal GitHub page

Taught by

Prof. Dr.-Ing. Lutz Eckstein, Bastian Lampe M.Sc. and Till Beemelsmanns M.Sc.

Reviews

Start your review of Automated and Connected Driving Challenges

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.