Title :
Advanced lane recognition-fusing vision and radar
Author :
Gern, A. ; Franke, Uwe ; Levi, Paul
Author_Institution :
DaimlerChrysler Res., Stuttgart, Germany
Abstract :
One major problem of the common vision-based lane recognition systems is their susceptibility to weather. These problems mainly stem from the fact, that they only look for road structures. From the position of other cars in front, the run of the curve can be estimated. This paper presents our fusion approach, that takes leading vehicles into account which have been detected by radar. The Kalman filter applied here does not only deliver improved measurements of the run of the curve, but also a precise estimate of the lateral position of the observed cars. This information can be used to improve the lane assignment of ACC systems
Keywords :
Kalman filters; automobiles; computer vision; pattern recognition; road vehicle radar; sensor fusion; transport control; Kalman filter; advanced lane recognition; data fusion; lateral position; observed cars; radar; road structures; vision-based lane recognition systems; weather; Augmented virtuality; Equations; Kalman filters; Position measurement; Radar tracking; Road transportation; Surface fitting; Surface texture; Vehicle detection; Weather forecasting;
Conference_Titel :
Intelligent Vehicles Symposium, 2000. IV 2000. Proceedings of the IEEE
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-6363-9
DOI :
10.1109/IVS.2000.898316
