Applies Dempster-Shafer Theory with conditional BPAs and Yager's combination rule, then variance-based sensitivity analysis, to represent and rank uncertainties in LiDAR detection for a SOTIF scenario.
Simulation-based performance evaluation of 3d object detection methods with deep learning for a lidar point cloud dataset in a sotif- related use case
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Uncertainty Representation in a SOTIF-Related Use Case with Dempster-Shafer Theory for LiDAR Sensor-Based Object Detection
Applies Dempster-Shafer Theory with conditional BPAs and Yager's combination rule, then variance-based sensitivity analysis, to represent and rank uncertainties in LiDAR detection for a SOTIF scenario.