Lectures

Automated and connected driving is a major topic in automotive research and industry at the moment. The module "Automated and Connected Driving Challenges (ACDC)"  introduces students to 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 ROS (Robot Operating System), which is a popular software framework for automated vehicle prototypes. On this basis, students then learn how to develop and integrate modules for sensor data processing, object fusion and tracking, vehicle guidance and V2X communication.  In particular, the students will:

• Develop functions for automated and connected vehicles using Python and C++
• Integrate their developed functions into the Robot Operating System
• Train Neural Networks for Computer Vision tasks with Tensorflow
• Learn how to use tools like: Linux, Terminal, ROS, RVIZ, Juypter Notebooks, Git

All course materials can be accessed on-demand through the MOOC portal https://edge.edx.org/ and https://jupyter.rwth-aachen.de. This allows self-paced learning throughout the semester. Frequent quizzes allow the learner to regularly test their comprehension of the materials.

While the course Automotive Engineering IV gives a general overview of automated and connected driving and presents more established aspects of the field, ACDC provides the possibility to get to know and work on the latest research challenges in automated and connected driving. In the subsequent and voluntary module "Automated and Connected Driving Challenges - Research Project", students may conduct their own a research resulting in a small research paper.

Previous knowledge expected:
Students should be familiar with at least one high-level programming language in advance (Java, Python, C++, ...).

This course replaces the previously offered courses "Self-Driving Lab I - Software Framework" and "Self-Driving Lab II - Algorithms" and incorporates their content.

Learning Outcomes (Level 1-2)

• Students can name and explain current research challenges in automated and connected driving.
• Students can name and describe the most important functions of automated and connected vehicles.
• Students can explain how different software modules in automated and connected vehicles interact.
• Students can explain the role of AI technology in automated and connected driving.
• Students can name and explain the basic features of the Robot Operating System.

Learning Outcomes (Level 3-6)

• Students are able to contribute to current research challenges in automated and connected driving.
• Students can program functions for automated and connected vehicles using Python and C++.
• Students can integrate their developed functions into the Robot Operating System.
• Students can train neural networks, e.g. with Tensorflow.
• Students are able to evaluate their developed functions.