ATTENTION: This is a web archive! The IMS Group was split up in 2018 and does not exist anymore. Recent work of former members can be found at the VR/AR Group and the Computer Vision Group.

Interactive Media Systems, TU Wien

Support Framework for Obstacle Detection on Autonomous Trains

Thesis by Michael Gschwandtner

Supervision by Andreas Uhl and Margrit Gelautz

Abstract

Autonomous driving vehicles are a rapidly emerging technlogy that will radically transform the face of public and personal transportation in the near future. This work is part of project autoBAHN, which has the goal to develop an autonomous driving train and in turn prevent small railroad branch lines from beeing shut down due to cost saving measures. The focus of research in the field of sensors used for autonomous vehicles is on the detection of obstacles. However, detecting obstacles is only a part of an autonomous driving vehicle. This work aims at providing the basis for making a complete autonomous driving train possible. This basis is a combination of sensor calibration techniques, track detection for railroads to classify obstacles and non-obstacles and simulation of sensor data for the verification of the individual underlying algorithms.

Reference

M. Gschwandtner: "Support Framework for Obstacle Detection on Autonomous Trains"; Supervisor, Reviewer: A. Uhl, M. Gelautz; Department of Computer Sciences, University of Salzburg, 2013; oral examination: 01-17-2013.

BibTeX

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