Scheible, Alexander (Ulm University), Griebel, Thomas (Ulm University), Buchholz, Michael (Universität Ulm)

Self-Monitored Detection Probability Estimation for the Labeled Multi-Bernoulli Filter

Scheduled for presentation during the Poster Session "Transportation Data Analysis and Calibration" (FrAT17), Friday, September 27, 2024, 10:30−12:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

Automated vehicles rely on their environment model, usually generated by a tracking module using sensor data, to make decisions. Therefore, estimating the accuracy of the tracking module is vital for the safe and reliable operation of the vehicle. This work makes a step towards this goal by providing a detection probability estimation method with a self-monitored quality assessment for the labeled multi-Bernoulli filter. We demonstrate the significance of the proposed quality index by comparing it with the actual estimation error calculated with ground truth data. This shows that the developed index is a meaningful value that can be computed online without ground truth data.