DocumentCode
3468115
Title
Multiple-model tracking for the detection of lane change maneuvers
Author
Weiss, Kristian ; Kaempchen, Nico ; Kirchner, Alexander
Author_Institution
Electron. Res. Dept., Volkswagen AG, Wolfsburg, Germany
fYear
2004
fDate
14-17 June 2004
Firstpage
937
Lastpage
942
Abstract
Volkswagen research has developed a system for vehicle surround perception which integrates different sensor data of the environment into a combined description by using a single model Kalman tracker. This paper deals with the extension of the tracking system by means of an interacting multiple-model algorithm (IMM) to improve the tracking stability during curves and to detect lane changes of the observed target vehicle. The applied IMM-tracker uses specialized models for lateral and longitudinal motion that are partly affected by curvature estimation. The technique is tested with recorded sequences of measurement data and shows robust tracking and well-fitting classification of the dynamical behavior of the targets.
Keywords
Kalman filters; probability; road vehicles; sensor fusion; target tracking; tracking filters; curvature estimation; dynamical behavior; lane change maneuver detection; lateral motion; longitudinal motion; measurement data sequences; multiple model algorithm; multiple model tracking; observed target vehicle; probability; robust tracking; sensor data fusion; single model Kalman tracker; target tracking; tracking stability; tracking system; vehicle surround perception; Change detection algorithms; Kalman filters; Motion estimation; Robustness; Sensor phenomena and characterization; Sensor systems; Stability; Target tracking; Testing; Vehicle detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium, 2004 IEEE
Print_ISBN
0-7803-8310-9
Type
conf
DOI
10.1109/IVS.2004.1336511
Filename
1336511
Link To Document