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Visual Map-based Localization applied to Autonomous Vehicles
KTH, School of Computer Science and Communication (CSC).
2015 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This thesis is carried out in the context of Advanced Driver Assistance Systems, and especially autonomous vehicles. Its aim is to propose a method to enhance localization of vehicles on roads. I suggests using a camera to detect lane markings, and to match these to a map to extract the corrected position of the vehicle.The thesis is divided in three parts dealing with: the map, the line detector and the evaluation. The map is based on the OpenStreetMap data. The line detector is a based on ridge detection. The results are compared with an Iterative Closest Point algorithm. It also focuses on implementing the components under a real-time constraint. Technologies such as ROS, for synchronization of the data, and CUDA, for parallelization, are used.

Place, publisher, year, edition, pages
Keyword [en]
localization, line detection, autonomous vehicle, adas, OpenStreetMap
National Category
Computer Science
URN: urn:nbn:se:kth:diva-174890OAI: diva2:859759
Available from: 2015-10-14 Created: 2015-10-08 Last updated: 2015-10-14Bibliographically approved

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