Using Dempster-Shafer-based modeling of object existence evidence in sensor fusion systems for advanced driver assistance systems

Abstract

In this contribution, we present an overview of modeling techniques for sensory existence evidence using the Dempster Shafer Theory of Evidence (DST). Several modeling aspects are examined. The purpose of this approach is to enhance the detection performance of a sensor fusion system in terms of detection rate versus false alarm rate. An integrated state and existence estimation algorithm is used which directly incorporates the DST-based sensory information. The advantages of this algorithm are evaluated using a sensor fusion and tracking system based on a large database of real-world sensor data.