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EEA-EV008 @ Aalto University

EEA-EV008 @ Aalto University

About

EEA-EV008: Visual Perception and Planning for Autonomous Driving is a graduate-level course at Aalto University covering the fundamental concepts and practical methods underlying autonomous driving systems. The course focuses on how autonomous vehicles perceive their environment and plan safe, intelligent actions, spanning topics such as visual sensing, scene understanding, localization, decision-making, motion planning, and control. The course combines theoretical foundations with practical implementation, giving students an opportunity to work with concepts and tools relevant to modern autonomous driving research and development.

  • Course Overview

    Course Level: Advanced Studies (5 cr)

    Department: Electrical Engineering and Automation (EEA)

    Institution: Aalto University

  • Course Listing

  • Learning Outcomes

    • Describe the architecture and key challenges of autonomous driving systems, including perception, planning, control, and localization.

    • Develop autonomous driving modules using ROS 2 and AutoDRIVE Ecosystem, including perception, planning, and control algorithms.

    • Implement deep learning models for perception tasks such as lane detection, object detection, segmentation, and depth estimation using multi-modal sensor data.

    • Design and evaluate motion planning strategies for autonomous navigation in simulated environments.

  • Course Content

    • Introduction to Autonomous Driving

    • Vehicle Dynamics and Control

    • Rigid Body Transformations

    • Localization

    • Path Planning

    • Motion Planning

    • Deep Learning Fundamentals

    • Object Detection, Segmentation, and Depth Estimation

    • Imitation Learning

Instructors
Dr. Shoaib Azam
shoaib.azam@aalto.fi
Course Instructor		 Dr. Ville Kyrki
ville.kyrki@aalto.fi
Course Instructor		 Furkan Yardımcı
furkan.yardimci@aalto.fi
Teaching Assistant

Resources

This course is powered by AutoDRIVE Ecosystem, where students work closely with Nigel — a 1:14 scale autonomous vehicle platform. Please see the accompanying video for a glimpse of Nigel in AutoDRIVE Ecosystem.

AutoDRIVE is envisioned to be an open, comprehensive, flexible and integrated cyber-physical ecosystem for enhancing autonomous driving research and education. It bridges the gap between software simulation and hardware deployment by providing the AutoDRIVE Simulator and AutoDRIVE Testbed, a well-suited duo for real2sim and sim2real transfer targeting vehicles and environments of varying scales and operational design domains. It also offers AutoDRIVE Devkit, a developer's kit for rapid and flexible development of autonomy algorithms using a variety of programming languages and software frameworks. For this course, students will develop their autonomous driving algorithms using the AutoDRIVE Devkit to interface with the AutoDRIVE Simulator in real-time.

The tech stack for this course has been released: