Carnegie Mellon Robotics Institute
Mei Chen, Todd Jochem, and Dean Pomerleau
tech. report CMU-RI-TR-97-21, Robotics Institute, Carnegie Mellon University, May, 1997
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| Abstract |
| AURORA is a vision-based system designed to warn a vehicle driver of psosible 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 the 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 |
Sponsor: NHTSA Grant ID: DTNH22-93-c-07023 Associated Center(s) / Consortia:
Vision and Autonomous Systems Center Associated Lab(s) / Group(s):
NavLab Associated Project(s):
AUtomotive Run-Off-Road Avoidance system Number of pages: 22 |
| Text Reference |
| Mei Chen, Todd Jochem, and Dean Pomerleau, "AURORA: A Vision-Based Roadway Departure Warning System," tech. report CMU-RI-TR-97-21, Robotics Institute, Carnegie Mellon University, May, 1997 |
| BibTeX Reference |
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@techreport{Chen_1997_446, author = "Mei Chen and Todd Jochem and Dean Pomerleau", title = "AURORA: A Vision-Based Roadway Departure Warning System", booktitle = "", institution = "Robotics Institute", month = "May", year = "1997", number= "CMU-RI-TR-97-21", address= "Pittsburgh, PA", } |
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