@inproceedings{Gerland2009ECC,
  abstract = {Frequently, the increasing level of automation requires a systematic
	consideration of numerous interacting components influenced by internal
	feedback mechanisms as well as interactions with human operators
	under varying environmental conditions. This places demands on modeling,
	which in general cannot be satisfied by traditional modeling concepts.
	In this paper, a model approach for complex technical systems is
	developed, which consists of two language layers. The first layer
	takes the physical knowledge of the technical system into account.
	The second one uses stochastic models in combination with superordinate
	higher-level terms to formulate properties concerning the overall
	system. By means of a case study dealing with the automation of mobile
	working machines, it is shown that this approach can be used to recognize
	driving situations under varying environmental conditions.},
  address = {Budapest, Hungary},
  author = {Gerland, Patrick and Schulte, Horst and Kroll, Andreas},
  booktitle = {European Control Conference (ECC)},
  comment = {DVD-ROM},
  interhash = {e1936b3ae8f4899ee6b6a3ec59b0d72f},
  intrahash = {9afcd16c4c8030772333fd482016bde8},
  isbn = {978-963-311-369-1},
  language = {english},
  month = {August 23--26},
  mrtnote = {peer, gerland},
  owner = {duerrbaum},
  pages = {1269--1274},
  publisher = {IEEE},
  title = {Probability-based global state detection of complex technical systems
	and application to mobile working machines},
  year = 2009
}