Abstract:
Most of the lane marking detection algorithms
reported in the literature are suitable for highway scenarios.
This paper presents a novel clustered particle filter based
approach to lane detection, which is suitable for urban streets in
normal traffic conditions. Furthermore, a quality measure for
the detection is calculated as a measure of reliability. The core of
this approach is the usage of weak models, i.e. the avoidance of
strong assumptions about the road geometry. Experiments were
carried out in Sydney urban areas with a vehicle mounted laser
range scanner and a ccd camera. Through experimentations,
we have shown that a clustered particle filter can be used to
efficiently extract lane markings.
