Paper Info
Title
Lane marking aided vehicle localization
Abstract
A localization system that exploits L1-GPS estimates, vehicle data, and features from a video camera as well as lane markings embedded in digital navigation maps is presented. A sensitivity analysis of the detected lane markings is proposed in order to quantify both the lateral and longitudinal errors caused by 2D-world hypothesis violation. From this, a camera observation model for vehicle localization is proposed. The paper presents also a method to build a map of the lane markings in a first stage. The solver is based on dynamical Kalman filtering with a two-stage map-matching process which is described in details. This is a software-based solution using existing automotive components. Experimental results in urban conditions demonstrate an significant increase in the positioning quality.
Year
DOI
Venue
2013
10.1109/ITSC.2013.6728444
ITSC
Keywords
Field
DocType
global positioning system,kalman filters,computer vision,image matching,sensitivity analysis,2d world hypothesis violation,li-gps estimates,automotive components,camera observation model,digital navigation maps,dynamical kalman filtering,lane marking aided vehicle localization system,lane markings detection,map matching process,video camera,kalman filtering,localization,digital maps
Computer vision,Digital mapping,Simulation,Kalman filter,Software,Artificial intelligence,Global Positioning System,Solver,Engineering,Video camera,Mobile mapping,Automotive industry
Conference
ISSN
Citations 
PageRank 
2153-0009
13
0.69
References 
Authors
5
4
Name
Order
Citations
PageRank
Tao, Z.1130.69
Philippe Bonnifait245255.82
Vincent Frémont312314.18
Javier Ibanez Guzman412817.14