Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
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
2015.
Keyword [en]
localization, line detection, autonomous vehicle, adas, OpenStreetMap
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-174890OAI: oai:DiVA.org:kth-174890DiVA: diva2:859759
External cooperation
INRIA Grenoble
Supervisors
Examiners
Available from: 2015-10-14 Created: 2015-10-08 Last updated: 2015-10-14Bibliographically approved

Open Access in DiVA

fulltext(2819 kB)1004 downloads
File information
File name FULLTEXT01.pdfFile size 2819 kBChecksum SHA-512
61d825de4c85ec7465bf8a90114e4ccd073744c61f37ed337ce36ad9ac088547efdd532ed9089f8ec0401aeca560d4fe7f2017346bd042cb4ec5350ddcc860ba
Type fulltextMimetype application/pdf

By organisation
School of Computer Science and Communication (CSC)
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 1004 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 305 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf