Binocular Stereopsis and Lane Marker Flow for Vehicle Navigation:
Lateral and Longitudinal Control
Quang-Tuan Luong, and
University of California at Berkeley, Technical Report UCB:CSD-94-804,
March 24, 1994
We propose a new approach for vision based longitudinal and lateral
vehicle control which makes extensive use of binocular stereopsis.
Longitudinal control --- i.e. maintaining a safe, constant distance
from the vehicle in front --- is supported by detecting and measuring
the distances to leading vehicles using binocular stereo. A known
camera geometry with respect to the locally planar road is used to map
the images of the road plane in the two camera views into alignment.
Any significant residual image disparity then indicates an object not
lying in the road plane and hence a potential obstacle. This
approach allows us to separate image features into those lying in the
road plane, e.g. lane markers, and those due to other objects. The
features which lie on the road are stationary in the scene and appear
to move only because of the egomotion of the vehicle. Measurements on
these features are used for dynamic update of (a) the camera
parameters in the presence of camera vibration and changes in road
slope (b) the lateral position of the vehicle with respect to the lane
markers. In the absence of this separation, image features due to
vehicles which happen to lie in the search zone for lane markers would
corrupt the estimation of the road boundary contours. This problem
has not yet been addressed by any lane marker based vehicle guidance
approach, but has to be taken very seriously, since usually one has to
cope with crowded traffic scenes where lane markers are often
obstructed by vehicles. Lane markers are detected and used for
lateral control, i.e. following the road while maintaining a constant
lateral distance to the road boundary. For that purpose we model the
road and hence the shape of the lane markers as clothoidal curves, the
curvatures of which we estimate recursively along the image sequence.
These curvature estimates also provides desirable look-ahead
information for a smooth ride in the car.
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Berkeley, May 26, 1994.
Last modified on Tuesday, November 20, 1996,