Title :
Robust vehicle tracking fusing radar and vision
Author :
Gern, Axel ; Franke, Uwe ; Levi, Paul
Author_Institution :
DaimlerChrysler Res., Stuttgart, Germany
Abstract :
Many driver assistance systems are based on vehicle detection and tracking including adaptive cruise control, collision warning and fully autonomous driving. A large detection range is required, especially while driving at higher speeds on highways. A reliable and precise detection is needed even under adverse weather conditions. In this paper we present a fusion approach combining radar and monocular image processing. The approach enables one to track vehicles up to a distance of 130 m and to assign them reliably to specific lanes.
Keywords :
automobiles; computer vision; object recognition; road vehicle radar; sensor fusion; tracking; collision warning; computer vision; driver assistance systems; lane recognition; monocular image processing; radar; sensor fusion; vehicle tracking; Adaptive control; Control systems; Programmable control; Radar detection; Radar tracking; Remotely operated vehicles; Road accidents; Road transportation; Robustness; Vehicle detection;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 2001. MFI 2001. International Conference on
Print_ISBN :
3-00-008260-3
DOI :
10.1109/MFI.2001.1013555