Systems and Algorithms for Autonomous Vehicles

Utbildningsfakta

Kod: 5EL283

The course provides an in-depth introduction to autonomous vehicles, addressing both the algorithms aspect and the systems aspect. The course consists of two parts. Part 1: Theory (5.5 hp). History and background of autonomous driving; perception-planning-control pipeline of autonomous vehicles; fundamentals of Machine Learning, Deep Learning and Reinforcement Learning; Convolutional Neural Networks for perception, including object classification, object detection, and segmentation; classic planning and control algorithms; Reinforcement Learning-based planning and control algorithms; safety and security issues; hardware and software platforms. Part 2: Lab Assignments (2.0 hp). Training and deployment of Deep Learning models for autonomous driving with a framework such as Tensorflow or PyTorch; implementation of part of the perception-planning-control pipeline in a simulation environment.

Behörighet

Admission to the course requires 120 credits of previous studies including courses in the field of Artificial Intelligence (AI) or Machine Learning of at least 7.5 credits

Utbildningstillfällen

Varje tillfälle har egna datum och villkor. Avslutade tillfällen behålls som historik och innebär inte att en ny ansökan är öppen.

• Systems and Algorithms for Autonomous Vehicles

  Umeå University

  Startdatum: 2 november 2026

  Slutdatum: 17 januari 2027

  Studietakt: 50 %