DocumentCode :
2487082
Title :
Lane departure detection for improved road geometry estimation
Author :
Schön, Thomas B. ; Eidehall, Andreas ; Gustafsson, Fredrik
Author_Institution :
Div. of Autom. Control, Linkoping Univ.
fYear :
0
fDate :
0-0 0
Firstpage :
546
Lastpage :
551
Abstract :
An essential part of future collision avoidance systems is to be able to predict road curvature. This can be based on vision data, but the lateral movement of leading vehicles can also be used to support road geometry estimation. This paper presents a method for detecting lane departures, including lane changes, of leading vehicles. This information is used to adapt the dynamic models used in the estimation algorithm in order to accommodate for the fact that a lane departure is in progress. The goal is to improve the accuracy of the road geometry estimates, which is affected by the motion of leading vehicles. The significantly improved performance is demonstrated using sensor data from authentic traffic environments
Keywords :
collision avoidance; computer vision; estimation theory; motion control; road vehicles; traffic engineering computing; CUSUM-test; Kalman filter; automotive tracking; change detection; collision avoidance system; lane departure detection; leading vehicles; road curvature; road geometry estimation; sensor data; state estimation; Filters; Geometry; Machine vision; Position measurement; Radar tracking; Road vehicles; Shape measurement; State estimation; Vehicle detection; Vehicle dynamics; Automotive tracking; CUSUM-test; Kalman filter; change detection; state estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2006 IEEE
Conference_Location :
Tokyo
Print_ISBN :
4-901122-86-X
Type :
conf
DOI :
10.1109/IVS.2006.1689685
Filename :
1689685
Link To Document :
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