Abstract
The requirements for a vehicle environment representation increase with the complexity of advanced driver assistance systems and automatic driving. The ability of the current traffic situation to interpret and predict is essential for being able to automatically derive reasonable decisions. As a consequence, a state of the art vehicle environment representation has to incorporate all relevant dynamic objects as well as static obstacles and context information. While dynamic objects are typically described by an object-based representation using state variables, static obstacles as well as free space area are commonly modeled using grid-based methods. This chapter gives an introduction into both of these concepts.
The chapter is organized as follows: First, the difference between function-oriented and modular fusion architectures is discussed. Afterwards, the joint integrated probabilistic data association (JIPDA) filter is introduced, which is one method to realize an object-based environment model incorporating both state and existence uncertainties. Further, the representation of static obstacles with occupancy grids is described in detail and the incorporation of measurements of different sensor types is illustrated. Finally, several hybrid environment representations are introduced and an example for a strictly modular architecture, the hierarchical modular environment perception, is presented.
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Dietmayer, K.C.J., Reuter, S., Nuss, D. (2016). Representation of Fused Environment Data. In: Winner, H., Hakuli, S., Lotz, F., Singer, C. (eds) Handbook of Driver Assistance Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-12352-3_25
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DOI: https://doi.org/10.1007/978-3-319-12352-3_25
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