Advanced lane recognition-fusing vision and radar

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.