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Prof. Dr.-Ing. Lutz Eckstein,
Bastian Lampe M.Sc.,
and
Till Beemelmanns M.Sc.
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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/webxe3/automated
What's inside
Learning objectives
- 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.
- 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.
- After completing the course, you will be able to
Syllabus
Week 1-3: Introduction & Tools
Introduction to current challenges in automated and connected driving
Introduction to the course tools and setup
Read more
Syllabus
Week 1-3: Introduction & Tools
Introduction to current challenges in automated and connected driving
Introduction to the course tools and setup
Read more
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
Vehicle Localization
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
We suggest you take between one and two weeks to recap the materials of the course and then to finish the exam. Of course, you may take the exam whenever you prefer, if you completed the course earlier than planned.
(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
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Focuses on automated and connected driving, a cutting-edge topic in automotive research and industry
Emphasizes hands-on learning through real-world examples and practical exercises
Taught by experienced professionals from the field, ensuring up-to-date knowledge and industry insights
Students will gain proficiency in using industry-standard tools like ROS, TensorFlow, and Docker
Tasks and exercises are designed to encourage creativity and exploration
Students can work independently or collaborate in groups to solve challenges
Save this course
Save Automated and Connected Driving Challenges to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Automated and Connected Driving Challenges with these
activities:
Connect with experts in autonomous driving
Show steps
Build your network and gain valuable insights by reaching out to professionals and researchers in the field of autonomous driving.
Show steps
-
Attend industry events and conferences
-
Join online communities and forums
-
Reach out to professors or researchers in your university
-
Connect with professionals on LinkedIn
Attend an industry conference
Show steps
Immerse yourself in the latest advancements and trends in autonomous driving by attending a relevant conference or industry event.
Show steps
-
Research upcoming conferences
-
Register for and attend the conference
-
Connect with professionals in the field
-
Attend workshops and presentations
Review Linear Algebra
Show steps
Strengthen your understanding of linear algebra, which is essential for various concepts covered in the course, such as vehicle localization and guidance.
Browse courses on
Linear Algebra
Show steps
-
Revise key concepts such as vectors, matrices, and transformations
-
Solve practice problems and exercises
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow ROS tutorials
Show steps
Deepen your understanding of ROS by following interactive tutorials and guides provided by the ROS community.
Browse courses on
Robot Operating System
Show steps
-
Install ROS on your system
-
Complete the ROS tutorials
-
Explore additional ROS resources
Practice Python exercises
Show steps
Enhance your understanding of Python syntax and improve your coding skills by solving a series of exercises and challenges.
Show steps
-
Review Python basics
-
Solve online coding challenges
-
Build small scripts or programs
Develop an object detection system
Show steps
Apply your learnings to a practical project by building an object detection system using the techniques covered in the course.
Browse courses on
Object Detection
Show steps
-
Gather a dataset of images
-
Train a machine learning model
-
Integrate the model into a real-time application
-
Evaluate the performance of your system
Write a blog post on autonomous driving
Show steps
Consolidate your understanding of autonomous driving by writing a blog post that summarizes the key concepts and your personal insights.
Browse courses on
Autonomous Driving
Show steps
-
Research the topic thoroughly
-
Outline and draft your blog post
-
Edit and proofread your post
-
Publish and promote your blog post
Contribute to the ROS community
Show steps
Engage with the wider ROS community by contributing to open source projects, reporting bugs, or suggesting improvements.
Browse courses on
Open Source
Show steps
-
Find an open ROS project
-
Identify a bug or improvement
-
Submit a pull request or issue
-
Review and respond to feedback
Connect with experts in autonomous driving
Show steps
Build your network and gain valuable insights by reaching out to professionals and researchers in the field of autonomous driving.
Show steps
Show steps
Show steps
- Attend industry events and conferences
- Join online communities and forums
- Reach out to professors or researchers in your university
- Connect with professionals on LinkedIn
Attend an industry conference
Show steps
Immerse yourself in the latest advancements and trends in autonomous driving by attending a relevant conference or industry event.
Show steps
Show steps
Show steps
- Research upcoming conferences
- Register for and attend the conference
- Connect with professionals in the field
- Attend workshops and presentations
Review Linear Algebra
Show steps
Strengthen your understanding of linear algebra, which is essential for various concepts covered in the course, such as vehicle localization and guidance.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Revise key concepts such as vectors, matrices, and transformations
- Solve practice problems and exercises
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow ROS tutorials
Show steps
Deepen your understanding of ROS by following interactive tutorials and guides provided by the ROS community.
Browse courses on
Robot Operating System
Show steps
Show steps
Show steps
- Install ROS on your system
- Complete the ROS tutorials
- Explore additional ROS resources
Practice Python exercises
Show steps
Enhance your understanding of Python syntax and improve your coding skills by solving a series of exercises and challenges.
Show steps
Show steps
Show steps
- Review Python basics
- Solve online coding challenges
- Build small scripts or programs
Develop an object detection system
Show steps
Apply your learnings to a practical project by building an object detection system using the techniques covered in the course.
Browse courses on
Object Detection
Show steps
Show steps
Show steps
- Gather a dataset of images
- Train a machine learning model
- Integrate the model into a real-time application
- Evaluate the performance of your system
Write a blog post on autonomous driving
Show steps
Consolidate your understanding of autonomous driving by writing a blog post that summarizes the key concepts and your personal insights.
Browse courses on
Autonomous Driving
Show steps
Show steps
Show steps
- Research the topic thoroughly
- Outline and draft your blog post
- Edit and proofread your post
- Publish and promote your blog post
Contribute to the ROS community
Show steps
Engage with the wider ROS community by contributing to open source projects, reporting bugs, or suggesting improvements.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Find an open ROS project
- Identify a bug or improvement
- Submit a pull request or issue
- Review and respond to feedback
Career center
Learners who complete Automated and Connected Driving Challenges will develop knowledge and skills
that may be useful to these careers:
Robotics Engineer
Robotics Engineer
Robotics Engineers design, build, maintain, and operate robots and robotic systems. The course's training in ROS, environment perception, and vehicle guidance provide you with the skills you need to contribute to the next generation of automated driving technology. In this role, you may be responsible for the design and development of automated driving systems, which include perception, planning, and control software, sensors, actuators, and mechanical components.
Software Engineer
Software Engineer
Software Engineers will develop and maintain the software that controls automated driving systems. This course will provide you with the skills you need to develop and integrate software modules for sensor data processing, object fusion & tracking, vehicle guidance, and connected driving. You will also learn how to use ROS, a popular software framework for automated vehicle prototypes.
Data Scientist
Data Scientist
Data Scientists will be responsible for collecting, cleaning, and analyzing data from automated driving systems. This course will provide you with the skills you need to train neural networks for environment perception tasks using TensorFlow. You will also learn how to use tools like Jupyter Notebooks and Git, which are essential for data science.
Systems Engineer
Systems Engineer
Systems Engineers will be responsible for integrating the different components of automated driving systems. This course will provide you with the skills you need to integrate your developed functions into the Robot Operating System (ROS). You will also learn how to use tools like Docker and RVIZ, which are essential for systems engineering.
Test Engineer
Test Engineer
Test Engineers will be responsible for testing and validating automated driving systems. This course will provide you with the skills you need to evaluate your developed functions. You will also learn how to use tools like ROS and RVIZ, which are essential for testing and validation.
Product Manager
Product Manager
Product Managers will be responsible for managing the development and launch of automated driving systems. This course will provide you with the skills you need to understand the technical challenges of automated driving and to communicate with engineers and other stakeholders.
Sales Engineer
Sales Engineer
Sales Engineers will be responsible for selling automated driving systems to customers. This course will provide you with the skills you need to understand the technical benefits of automated driving and to communicate with potential customers.
Marketing Manager
Marketing Manager
Marketing Managers will be responsible for developing and executing marketing campaigns for automated driving systems. This course will provide you with the skills you need to understand the target market for automated driving and to develop effective marketing messages.
Business Development Manager
Business Development Manager
Business Development Managers will be responsible for identifying and developing new business opportunities for automated driving systems. This course will provide you with the skills you need to understand the business case for automated driving and to develop relationships with potential partners.
Technical Writer
Technical Writer
Technical Writers will be responsible for creating documentation for automated driving systems. This course will provide you with the skills you need to write clear and concise technical documentation.
User Experience Designer
User Experience Designer
User Experience Designers will be responsible for designing the user interface for automated driving systems. This course will provide you with the skills you need to understand the user experience of automated driving and to design interfaces that are safe and easy to use.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts will be responsible for ensuring the quality of automated driving systems. This course will provide you with the skills you need to test and validate automated driving systems and to identify and fix defects.
Project Manager
Project Manager
Project Managers will be responsible for planning and executing automated driving projects. This course will provide you with the skills you need to manage projects effectively and to deliver successful results.
Operations Manager
Operations Manager
Operations Managers will be responsible for the day-to-day operations of automated driving systems. This course will provide you with the skills you need to manage operations effectively and to ensure that automated driving systems are safe and reliable.
Financial Analyst
Financial Analyst
Financial Analysts will be responsible for analyzing the financial performance of automated driving systems. This course will provide you with the skills you need to understand the financial implications of automated driving and to make sound investment decisions.
For more career information including salaries, visit:
OpenCourser.com/course/webxe3/automated
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Automated and Connected Driving Challenges.
Provides a comprehensive overview of machine learning for robotics, which is essential for developing automated driving systems.
Save
Provides a comprehensive overview of deep learning, a subfield of machine learning that is essential for developing automated driving systems.
Provides a comprehensive overview of probabilistic robotics, which is essential for developing automated driving systems.
Provides a comprehensive overview of the fundamentals of robotics, computer vision, and control, which are essential for developing automated driving systems.
Save
Provides a comprehensive overview of computer vision algorithms and applications. It valuable resource for anyone who wants to learn more about this field, which is essential for developing automated driving systems.
Provides a comprehensive overview of the fundamentals of automotive electronics, which is essential for developing automated driving systems.
Save
Provides a comprehensive overview of the fundamentals of robotics, which is essential for developing automated driving systems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/webxe3/automated
Share
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Effort
3 to 8 hours per week for 15 weeks
Level
Advanced
Via
edX
Institution
RWTH Aachen University
Instructors
Prof. Dr.-Ing. Lutz Eckstein
Bastian Lampe M.Sc.
Till Beemelmanns M.Sc.
Language
English
Transcript
English
Good to know
Focuses on automated and connected driving, a cutting-edge topic in automotive research and industry
Emphasizes hands-on learning through real-world examples and practical exercises
Taught by experienced professionals from the field, ensuring up-to-date knowledge and industry insights
Students will gain proficiency in using industry-standard tools like ROS, TensorFlow, and Docker
Tasks and exercises are designed to encourage creativity and exploration
Students can work independently or collaborate in groups to solve challenges
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