Title :
RALPH: rapidly adapting lateral position handler
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
Nearly 15,000 people die each year in the US in single vehicle roadway departure crashes. These accidents are often caused by driver inattention, or driver impairment (e.g. fatigued or intoxicated drivers). A system capable of warning the driver when the vehicle starts to depart the roadway, or controlling the lateral position of the vehicle to keep it in its lane, could potentially eliminate many of these crashes. This paper presents a system called RALPH (Rapidly Adapting Lateral Position Handler) which decomposes the problem of steering a vehicle into three steps, 1) sampling of the image, 2) determining the road curvature, and 3) determining the lateral offset of the vehicle relative to the lane center. The output of the later two steps are combined into a steering command, which can be compared with the human driver´s current steering direction as part of a road departure warning system, or sent directly to the steering motor
Keywords :
image sampling; position control; road vehicles; RALPH; driver impairment; driver inattention; image sampling; lateral offset; rapidly adapting lateral position handler; road curvature; road departure warning system; single vehicle roadway departure crashes; steering command; Control systems; Humans; Image sampling; Machine learning; Machine vision; Road accidents; Road vehicles; Robots; Vehicle crash testing; Vehicle driving;
Conference_Titel :
Intelligent Vehicles '95 Symposium., Proceedings of the
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2983-X
DOI :
10.1109/IVS.1995.528333