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Automated and Connected Driving Challenges

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.

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There is one session available:

After a course session ends, it will be archivedOpens in a new tab.
Starts Apr 12
Ends Sep 28
Enroll

Automated and Connected Driving Challenges

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.

15 weeks
3–8 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

After a course session ends, it will be archivedOpens in a new tab.
Starts Apr 12
Ends Sep 28
Enroll
Automated and Connected Driving Challenges

About this course

Skip About this course

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.

At a glance

  • Institution: RWTHx
  • Subject: Engineering
  • Level: Advanced
  • Prerequisites:
    • Basic linear algebra and calculus skills are advantageous
    • Basic programming skills with Python and C++ are advantageous

    • Basic skills in using Linux and command line interfaces are advantageous

    • A Linux operating system as a native operating system or, e.g., as a virtual machine, is necessary to execute programming exercises and to work with ROS. We provide instructions to set up the coding environment on your computer.

    • If possible, you should use a computer with an x86 CPU architecture. There is only limited support for machines with an ARM CPU architecture (Mac M1, M2 etc).

  • Language: English
  • Video Transcript: English

What you'll learn

Skip What you'll learn

After completing the course, you will be able to

  • contribute to current research challenges in automated and connected driving;
  • program functions for automated and connected driving using Python & C++;
  • integrate your developed functions into the Robot Operating System;
  • train neural networks, e.g. with TensorFlow;
  • evaluate your developed functions.

Syllabus

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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 10-11: Vehicle Guidance

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

Week 12-13: Connected Driving

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

Week 14-15: 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

About the instructors

Who can take this course?

Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

Ways to take this course

Choose your path when you enroll.
Verified Track
Audit Track

Price

$50 USD

Free

Access to course materials

Unlimited

Limited

Expires on Jul 26

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edX support

Shareable certificate upon completion

Graded assignments and exams

Read our FAQsin a new tab about frequently asked questions on these tracks.

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