Aktuelles - Papers

14.05.20 Kategorie: Papers

Genauigkeitscharakterisierung der Fahrzeugzustandsabschätzung aus Luftbildern

E. Sánchez, M. Botsch, Friedrich Kruber, Technische Hochschule Ingolstadt | Dr. Bertold Huber, GeneSys Elektronik GmbH | Andrés García, Universidad de Castilla-La Mancha/Spain


Form des Autos, wie sie von Mask-RCNN erkannt wird (orange gestrichelte Linie)

Form des Autos, wie sie von Mask-RCNN erkannt wird (orange gestrichelte Linie)

Sichtlinie des UAV (rot), die gesehene Fahrzeugposition (grün) und die wahre Fahrzeugposition (blau)

Sichtlinie des UAV (rot), die gesehene Fahrzeugposition (grün) und die wahre Fahrzeugposition (blau)


Abstract 

Due to their capability of acquiring aerial imagery, camera-equipped Unmanned Aerial Vehicles (UAVs) are verycost-effective tools for acquiring traffic information. However, not enough attention has been given to the validation of theaccuracy of these systems.

In this paper, an analysis of the most significant sources of error is done. This includes three key components. First, a vehicle state estimation by means of statistical filtering. Second, a quantification of the most significant sources of error. Third, a benchmark of the estimated state compared with state-of-the-art reference sensors.

This work presents ways to minimize the errors of the most relevant sources. With these error reductions, camera-equipped UAV sare very attractive tools for traffic data acquisition. The test data and the source code are made publicly available.