Automated and Connected Driving Challenges from edX

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.

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

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

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

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

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Build your network and gain valuable insights by reaching out to professionals and researchers in the field of autonomous driving.

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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

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Immerse yourself in the latest advancements and trends in autonomous driving by attending a relevant conference or industry event.

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Research upcoming conferences
Register for and attend the conference
Connect with professionals in the field
Attend workshops and presentations

Review Linear Algebra

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Strengthen your understanding of linear algebra, which is essential for various concepts covered in the course, such as vehicle localization and guidance.

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Revise key concepts such as vectors, matrices, and transformations
Solve practice problems and exercises

Five other activities

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Follow ROS tutorials

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Deepen your understanding of ROS by following interactive tutorials and guides provided by the ROS community.

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Install ROS on your system
Complete the ROS tutorials
Explore additional ROS resources

Practice Python exercises

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Enhance your understanding of Python syntax and improve your coding skills by solving a series of exercises and challenges.

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Review Python basics
Solve online coding challenges
Build small scripts or programs

Develop an object detection system

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Apply your learnings to a practical project by building an object detection system using the techniques covered in the course.

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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

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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

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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

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Engage with the wider ROS community by contributing to open source projects, reporting bugs, or suggesting improvements.

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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 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.

See salaries and explore the career path for Robotics 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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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