Abstract
More and more driver assistance systems are based on a fusion of multiple environment perception sensors. This chapter gives an overview about the objectives of sensor data fusion approaches, explains the main components involved in the perception process, and explains the special topics that need to be taken into consideration in developing a multi-sensor fusion system for driver assistance systems. Focus is put on the topics of data association, tracking, classification, and the underlying architecture. The architecture strongly influences the costs, performance, and the development process of a multi-sensor fusion system. As there are no deterministic methods that guarantee an optimal solution for developing an architecture, the chapter gives an overview of established, general architecture patterns in the field of sensor data fusion and discusses their benefits and drawbacks.
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Darms, M. (2015). Data Fusion of Environment-Perception Sensors for ADAS. In: Winner, H., Hakuli, S., Lotz, F., Singer, C. (eds) Handbook of Driver Assistance Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-09840-1_24-1
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DOI: https://doi.org/10.1007/978-3-319-09840-1_24-1
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