2019/02/12 by Johannes Müller, Müller, Johannes, Michael Gabb +3 · 1 citation
Computer Science · #Bayesian Modeling and Causal Inference #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #FOS: Electrical engineering #Multiagent Systems (cs.MA) #Signal Processing (eess.SP) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1903.01556
openalex publication_date 2019/02/12 · openalex created_date 2022/07/29 · openalex updated_date 2026/07/28
Use of cooperative information, distributed by road-side units, offers large\npotential for intelligent vehicles (IVs). As vehicle automation progresses and\ncooperative perception is used to fill the blind spots of onboard sensors, the\nquestion of reliability of the data becomes increasingly important in safety\nconsiderations (SOTIF, Safety of the Intended Functionality).\n This paper addresses the problem to estimate the reliability of cooperative\ninformation for in-vehicle use. We propose a novel method to infer the\nreliability of received data based on the theory of Subjective Logic (SL).\nUsing SL, we fuse multiple information sources, which individually only provide\nmild cues of the reliability, into a holistic estimate, which is statistically\nsound through an end-to-end modeling within the theory of SL.\n Using the proposed scheme for probabilistic SL-based fusion, IVs are able to\nseparate faulty from correct data samples with a large margin of safety. Real\nworld experiments show the applicability and effectiveness of our approach.\n