Carnegie Mellon University
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AUtomotive Run-Off-Road Avoidance system (AURORA)
This project is no longer active.
Head: Dean Pomerleau
Contact: Mei Chen
Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
Associated center(s) / consortia:
 Vision and Autonomous Systems Center (VASC)
Associated lab(s) / group(s):
Aurora employs a downward looking vision system consisting of a color video camera with a wide angle lens, a digitizer, and a Sun Sparc portable workstation.

By applying a novel template correlation method, it is able to reliably track lane markers on the road at 60 Hz and estimate the vehicle lateral displacement within an average absolute error of 0.8cm.

Based on this estimation, the time to lane crossing is calculated for each image field, triggering a warning alarm when it falls below a threshold.

Currently there are three warning modalities: visual, audible, and haptic (vibrating the steering wheel).