DocumentCode
3504369
Title
Vehicle localization using road markings
Author
Tao Wu ; Ranganathan, A.
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
fYear
2013
fDate
23-26 June 2013
Firstpage
1185
Lastpage
1190
Abstract
Reliable lane-level localization is a requirement for many driver-assistance methods as well as for autonomous driving. Localization using cameras is desirable due to ubiquity and cheapness of sensors but is hard to achieve reliably. We propose a method towards reliable visual localization using traffic signs painted on the road such as arrows, pedestrian crossings, and speed limits. These road markings are relatively easily detected since they are designed to be highly conspicuous. Our method automatically recognizes road markings and uses features detected within them to compute the location of the vehicle. This provides an absolute global localization if the road markings have been surveyed before hand, and relative positioning information otherwise. We demonstrate using experiments and with groundtruth data that our method provides accurate lane-level visual localization under various lighting conditions and using various types of road markings.
Keywords
feature extraction; lighting; object detection; object recognition; pose estimation; traffic engineering computing; feature detection; global localization; lane-level visual localization; lighting conditions; relative positioning information; reliable visual localization; road markings automatic recognition; traffic signs; vehicle localization; Boosting; Cameras; Estimation; Global Positioning System; Lighting; Roads; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium (IV), 2013 IEEE
Conference_Location
Gold Coast, QLD
ISSN
1931-0587
Print_ISBN
978-1-4673-2754-1
Type
conf
DOI
10.1109/IVS.2013.6629627
Filename
6629627
Link To Document