Advanced lane recognition-fusing vision and radar

Author

Gern, A. ; Franke, Uwe ; Levi, Paul

Author_Institution

DaimlerChrysler Res., Stuttgart, Germany

fYear

2000

fDate

2000

Firstpage

45

Lastpage

51

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Vehicles Symposium, 2000. IV 2000. Proceedings of the IEEE

Conference_Location

Dearborn, MI

Print_ISBN

0-7803-6363-9

Type

conf

DOI

10.1109/IVS.2000.898316

Filename

898316