The objective of this paper is the modelling of an unbounded environment of a human-driven car that may contain multilevel structures such as bridges or parking decks. Such a model might be used by a driver assistant system (DAS) where one drives through an urban environment, requests for an assistance and the DAS should immediatly be able to give the user the required support. E.g. it can guide through a narrow passage or a turn. For such an assistance an environment model is needed that runs in real-time. But to keep the system at low cost the required memory should be as small as possible. Hence the algorithm should be optimized with respect to computational power and memory consumption. A new approach is proposed that models the environment by incrementally adding small tiles at places where obstacles created measurements. Each tile contains an occupancy grid and some neighbourhood relations. By modelling the world this way, a compact representation of the environment is created that is aligned at the user-given trajectory and the allocation of obstacles. By using a grid based algorithm efficient and hence fast techniques can be used to work on the world representation. Also an extension is introduced to restrict the required memory to a given limit and concurrently map the local obstacles but avoids any transformation of historic data. A comparision with state of the art algorithms was made and the capability of the proposed algorithm is demonstrated with some experimental results.
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