AUtomotive Run-Off-Road Avoidance system - Robotics Institute Carnegie Mellon University
Graphical depiction of the AUtomotive Run-Off-Road Avoidance system project
AUtomotive Run-Off-Road Avoidance system
Project Head:

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).

Displaying 3 Publications

1997
J. A. Hadden, J. H. Everson, D. B. Pape, V. K. Narendran, and Dean Pomerleau
Conference Paper, Proceedings of 30th International Symposium on Automotive Technology and Automation, pp. 343 - 350, June, 1997
Mei Chen, Todd Jochem, and Dean Pomerleau
Tech. Report, CMU-RI-TR-97-21, Robotics Institute, Carnegie Mellon University, May, 1997
1995
Mei Chen, Todd Jochem, and Dean Pomerleau
Conference Paper, Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 1, pp. 243 - 248, August, 1995

current head

current contact