Autonomous vehicles have a great influence on our life. These vehicles are more convenient, more energy efficient providing higher safety level and cheaper driving solutions. In addition, decreasing the generation of CO2, and the risk vehicular accidents are other benefits of autonomous vehicles. “Design of Autonomous Systems” is a practical course aiming to give a broad understanding of the wide area of autonomous vehicles and the foundational knowledge in the topic areas required to understand and develop autonomous vehicles.

The course consists of 6 lectures in which each lecture has a specialized lab.
1. Image processing with OpenCV (line/edge/corner detection, distance estimation)
2. Sensor fusion using Kalman filtering techniques
3. Perception (object detection and image classification by using Keras)
4. Controlling the vehicle by using convolutional neural networks as an end-to-end solution
5. Obstacle avoidance algorithms
6. Vehicle-to-Vehicle communication

After the course, the student will be able to:
1. Explain how an autonomous system works and describe important components.
2. Analyze how different components contribute to the autonomy of a system.
3. Explain and apply common techniques and the theory behind them in the four topic areas Control and Decision making, Sensing and Perception, and V2V communication
4. Explain important model classes, key system properties, and basic control strategies.
5. Analyze the industrial and societal impact of autonomous systems