TY - GEN
T1 - Fusion of laserscannner and video based lanemarking detection for robust lateral vehicle control and lane change maneuvers
AU - Homm, Florian
AU - Kaempchen, Nico
AU - Burschka, Darius
PY - 2011
Y1 - 2011
N2 - The knowledge about lanes and the exact position on the road is fundamental for many advanced driver assistance systems. In this paper, a novel iterative histogram based approach with occupancy grids for the detection of multiple lanes is proposed. In highway scenarios, our approach is highly suitable to determine the correct number of all existing lanes on the road. Additionally, the output of the laserscannner based lane detection is fused with a production-available vision based system. It is shown that both sensor systems perfectly complement each other to increase the robustness of a lane tracking system. The achieved accuracy of the fusion system, the laserscannner and video based system is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control applications.
AB - The knowledge about lanes and the exact position on the road is fundamental for many advanced driver assistance systems. In this paper, a novel iterative histogram based approach with occupancy grids for the detection of multiple lanes is proposed. In highway scenarios, our approach is highly suitable to determine the correct number of all existing lanes on the road. Additionally, the output of the laserscannner based lane detection is fused with a production-available vision based system. It is shown that both sensor systems perfectly complement each other to increase the robustness of a lane tracking system. The achieved accuracy of the fusion system, the laserscannner and video based system is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control applications.
UR - http://www.scopus.com/inward/record.url?scp=79960759124&partnerID=8YFLogxK
U2 - 10.1109/IVS.2011.5940424
DO - 10.1109/IVS.2011.5940424
M3 - Conference contribution
AN - SCOPUS:79960759124
SN - 9781457708909
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 969
EP - 974
BT - 2011 IEEE Intelligent Vehicles Symposium, IV'11
T2 - 2011 IEEE Intelligent Vehicles Symposium, IV'11
Y2 - 5 June 2011 through 9 June 2011
ER -