  Evidential grids have recently shown interesting properties for mobile object
perception. Evidential grids are a generalisation of Bayesian occupancy grids
using Dempster- Shafer theory. In particular, these grids can handle
efficiently partial information. The novelty of this article is to propose a
perception scheme enhanced by geo-referenced maps used as an additional source
of information, which is fused with a sensor grid. The paper presents the key
stages of such a data fusion process. An adaptation of conjunctive combination
rule is presented to refine the analysis of the conflicting information. The
method uses temporal accumulation to make the distinction between stationary
and mobile objects, and applies contextual discounting for modelling
information obsolescence. As a result, the method is able to better
characterise the occupied cells by differentiating, for instance, moving
objects, parked cars, urban infrastructure and buildings. Experiments carried
out on real- world data illustrate the benefits of such an approach.
