Evaluation method of grid based representation from sensor data

A prerequisite for driver assistance applications is a high reliable and comprehensive description of the surrounding environment. The quality of the environmental description depends on the accuracy, reliability and the interpretation of the sensors 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 to determine which inverse sensor model represents the most accurate and concise interpretation and which evaluation method (for the global, near, middle or far field) is optimal.