[ 993TAMRIASU19 ] UE Introduction to Autonomous Systems

Workload Education level Study areas Responsible person Hours per week Coordinating university
1,5 ECTS M1 - Master's programme 1. year (*)Artificial Intelligence Luigi Del Re 1 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Artificial Intelligence 2019W
Objectives This course is intended to provide a general overview for engineers on the main aspects of automation of driving functions. While autonomous driving is a widely discussed issue at the moment, it is not a topic only for road traffic, indeed methods have been developed in different fields ranging from UAVs, to robots and of course to automotive.

The key idea of automation - in general - is to perform an action a skilled human operator could, but better/faster or more reliably. No automation removes the physical constraints, and sometimes new ones are added by the limited operation properties of the components involved, which, by the way, are also subject to errors and even failure.

Therefore, some expectations from automated functions are unrealistic, no automation system can guarantee no accidents in traffic, especially in mixed traffic conditions. Still, automation can offer enormous advantages as automated systems do not get tired, unattentive or distracted and can react much faster.

  • Setup of an inverse vehicle model in Simulink and analysis of its ability to replicate real measurements
  • Computation of optimum driving profiles using DP
  • Test of a ADF for performance
  • Prediction models using our BN toolbox;
  • Importance sampling
  • Simulators
Criteria for evaluation Homework, Written exam
Methods Group work, autonomous problem solving
Language English
Study material Homework Instructions, Lecture notes and slides
Changing subject? No
On-site course
Maximum number of participants 35
Assignment procedure Direct assignment