  For an autonomous vehicle, situation understand-ing is a key capability
towards safe and comfortable decision-making and navigation. Information is in
general provided bymultiple sources. Prior information about the road topology
andtraffic laws can be given by a High Definition (HD) map whilethe perception
system provides the description of the spaceand of road entities evolving in
the vehicle surroundings. Incomplex situations such as those encountered in
urban areas,the road user behaviors are governed by strong interactionswith the
others, and with the road network. In such situations,reliable situation
understanding is therefore mandatory to avoidinappropriate decisions.
Nevertheless, situation understandingis a complex task that requires access to
a consistent andnon-misleading representation of the vehicle surroundings.
Thispaper proposes a formalism (an interaction lane grid) whichallows to
represent, with different levels of abstraction, thenavigable and interacting
spaces which must be considered forsafe navigation. A top-down approach is
chosen to assess andcharacterize the relevant information of the situation. On
a highlevel of abstraction, the identification of the areas of interestwhere
the vehicle should pay attention is depicted. On a lowerlevel, it enables to
characterize the spatial information in aunified representation and to infer
additional information inoccluded areas by reasoning with dynamic objects.
