Deep learning for autonomous vehicles

Summary

Deep Learning (DL) is the subset of Machine learning reshaping the future of transportation and mobility. In this class, we will show how DL can be used to teach autonomous vehicles to detect objects, make predictions, and make decisions. (Fun fact: this summary is powered by DL)

Content

Keywords

Deep Learning, Autonomous Vehicle, Artificial intelligence, Machine learning, Self-driving car, human-robot tandem race

Learning Prerequisites

Required courses

• Knowledge of Python
• Understanding of linear algebra and calculus
• Introductory knowledge of Machine Learning concepts

Learning Outcomes

By the end of the course, the student must be able to:

• Define the fundamental steps behind an AI-driven system
• Design the building steps of an autonomous vehicle
• Implement an algorithm for each step
• Explain and understand the challenges and ethical impacts

Transversal skills

• Set objectives and design an action plan to reach those objectives.
• Communicate effectively, being understood, including across different languages and cultures.
• Demonstrate the capacity for critical thinking

Teaching methods

Ex cathedra

Expected student activities

• Attend lectures and participate in discussions
• Complete weekly programming assignments
• Work on hands-on projects to apply deep learning techniques to autonomous vehicle tasks
• Engage in group projects and present findings
• Participate in a final project showcasing the application of deep learning in autonomous vehicles

Assessment methods

- Lab projects (Individual): 30%

- Midterm (Individual): 30%

- Final project (in group): 40%

Supervision

Resources

Virtual desktop infrastructure (VDI)

No

Notes/Handbook

Online Resources: Access to online courses, tutorials, and documentation for deep learning frameworks

Moodle Link

• https://go.epfl.ch/CIVIL-459

Prerequisite for

• Advanced Courses: This course prepares students for more advanced topics in AI, robotics, and control systems
• Industry Roles: Equips students with skills relevant for careers in autonomous vehicle development, robotics engineering, and AI research
• Research Projects: Provides a foundation for conducting research in deep learning applications within the field of autonomous systems