The
PRELAT project
Aim: To
develop methods for accurate lateral truck positioning
Brief description
In this project, we are
using stochastic optimization algorithms and image
processing in order to obtain accurate estimates of the lateral
position of a truck.
Background and
motivation
The longitudinal
position (i.e. the position along the road) of a vehicle
can typically be estimated quite accurately using GPS
(perhaps augmented with odometry to handle GPS signal
loss). However, obtaining an accurate estimate of a
vehicle's lateral position, i.e. its position in
the lane(s), perpendicular to the road tangent, is more
challenging, as the (standard) GPS signal is not
sufficiently accurate for such measurements. Knowledge
of the lateral position is essential for the development
of autonomous vehicles.
Detailed description
In this project, we are
using landmark-based orientation, based on
camera images, in order to estimate the lateral
position of a vehicle (and, perhaps, its current
heading (yaw) angle as well).
The
project started in August
2015. More information
will be posted in the
Autumn of 2015.
Participants
Mattias Wahde
+ 1 PhD student (hiring in progress)
Last Update: 20150804,
08.00