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Abstract

AURORA is a vision-based system designed to warn a vehicle driver of possible impending roadway departure accidents. It employs a downward looking color video camera with a wide angle lens, a digitizer, and a portable Sun Sparc workstation. Using a binormalized adjustable template correlation algorithm, it reliably detects lane markers on structured roads at 60 Hz. A time-to-lane-crossing (TLC) measurement is calculated for each image based on the estimation of vehicle's lateral position and velocity. This measurement is used to trigger an alarm when the TLC falls below a preset threshold. Promising results have been achieved under a variety of weather and lighting conditions, on many road types.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): NavLab

Associated Project(s): AUtomotive Run-Off-Road Avoidance system

Text Reference

Mei Chen, Todd Jochem, and Dean Pomerleau, "AURORA: A Vision-Based Roadway Departure Warning System," IEEE Conference on Intelligent Robots and Systems, Human Robot Interaction and Cooperative Robots, August, 1995, pp. 243 - 248.

BibTeX Reference

@inproceedings{Chen_1995_610,
   author = "Mei Chen and Todd Jochem and Dean Pomerleau",
   title = "AURORA: A Vision-Based Roadway Departure Warning System",
   booktitle = "IEEE Conference on Intelligent Robots and Systems, Human Robot Interaction and Cooperative Robots",
   pages = "243 - 248",
   month = "August",
   year = "1995",
   volume = "1",
}

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