Evidence Based Evaluation Method for Grid-based Environmental Representation

Future driver assistance applications and safety systems require a high reliable and comprehensive description of the surrounding environment. The quality of this environmental description depends on the accuracy, reliability and the interpretation of the sensor's measurements. In this paper an evaluation method is introduced based on two quality metrics derived from the Dempster-Shafer theory. Applying these quality metrics different inverse sensor models are evaluated and compared in order to determine which inverse sensor model represents the most reliable and the most comprehensive interpretation, which application area (near, middle, far field) is optimal and which discrepancy to an optimal representation is achieved.