Visual Processing for Autonomous Driving

Henry Schneiderman and M. Nashman
Proceedings of IEEE Workshop on Applications of Computer Vision, December, 1992, pp. 164 - 171.


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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

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): NavLab
Number of pages: 8

Text Reference
Henry Schneiderman and M. Nashman, "Visual Processing for Autonomous Driving," Proceedings of IEEE Workshop on Applications of Computer Vision, December, 1992, pp. 164 - 171.

BibTeX Reference
@inproceedings{Schneiderman_1992_1031,
   author = "Henry Schneiderman and M. Nashman",
   title = "Visual Processing for Autonomous Driving",
   booktitle = "Proceedings of IEEE Workshop on Applications of Computer Vision",
   pages = "164 - 171",
   month = "December",
   year = "1992",
}