Tischler, KarinVogt, Heike S.Herzog, OttheinRödiger, Karl-HeinzRonthaler, MarcKoschke, Rainer2019-05-152019-05-152007978-3-88579-206-1https://dl.gi.de/handle/20.500.12116/22470Negative information provides important additional knowledge that is not exploited for sensor data fusion tasks by default. This paper presents a new approach to incorporate such information about unoccupied, observed areas or missing measurements in the Kalman filtering process. For this purpose, a combination with a grid-based method is proposed to generate a visibility map. This enables a plausibility check and an enhanced understanding for the collaborative perception of the environment with multiple cognitive vehicles. Results from a realistic traffic simulation are presented.enText/Conference Paper1617-5468