Multi Level Processing Methodology for Automotive Applications
Ullrich Scheunert, Philipp Lindner, Heiko Cramer, Thomas Tatschke, Aristomenis Polychronopoulos, Gerd Wanielik
IEEE 9th International Conference on intelligent Transportation Systems
17 - 20 September 2006
Abstract:The fusion of data from different sensorial sources is nowadays an often-used method to increase robustness and reliability of automatic environmental perception. The project ProFusion2, which is a horizontal subproject in the IP PReVENT (funded by the EC) was created to enhance fusion techniques and algorithms beyond the current state-of-the-art. The enhancement of the algorithms is strongly connected with the creation of a methodology to describe vehicle environments in an adequate manner to meet the requirements of robustness and reliability. In this paper, the definition of such a general environmental description is proposed and an according general data structure is introduced. This data structure is able to handle all kind of information occurring in a data fusion process. Additionally, an output structure of the perception system is proposed to work as an interface to the applications.
The ProFusion2 community suggested a model for sensor data fusion in compliance with the Joint Directors of Laboratories (JDL) model which is a widely known model for information fusion systems.