DocumentCode :
3336455
Title :
Visual processing for autonomous driving
Author :
Schneiderman, Henry ; Nashman, Marilyn
Author_Institution :
Robot Syst. Div., Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
fYear :
1992
fDate :
30 Nov-2 Dec 1992
Firstpage :
164
Lastpage :
171
Abstract :
Describes a visual processing algorithm that supports autonomous road following. The algorithm requires that lane markings be present and attempts to track the lane markings on both lane boundaries. There are three stages of computation: extracting edges; matching extracted edge points with a geometric model of the road, and updating the geometric road model. All processing is confined to the 2-D image plane. No information about the motion of the vehicle is used. This algorithm has been implemented and tested using video taped road scenes. It performs robustly for both highways and rural roads. The algorithm runs at a sampling rate of 15 Hz and has a worst case latency of 139 milliseconds (ms). The algorithm is implemented under the NASA/NBS Standard Reference Model for Telerobotic Control System Architecture (NASREM) architecture and runs on a dedicated vision processing engine and a VME-based microprocessor system
Keywords :
computer vision; mobile robots; road vehicles; 2-D image; autonomous driving; autonomous road following; lane markings; visual processing algorithm; Data mining; Delay; Image sampling; Layout; NASA; Road transportation; Robustness; Solid modeling; Testing; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications of Computer Vision, Proceedings, 1992., IEEE Workshop on
Conference_Location :
Palm Springs, CA
Print_ISBN :
0-8186-2840-5
Type :
conf
DOI :
10.1109/ACV.1992.240315
Filename :
240315
Link To Document :
بازگشت