StudiesCompleted Theses
Laserscanner-basierte Prädiktion von Passantenbewegungen durch Filterung und Klassifikation der Körperhaltung

Laser scanner-based prediction of pedestrian movements by filtering and classifying posture

Led by:  Claus Brenner, Steffen Busch
Team:  Matthias Fahrland
Year:  2019
Is Finished:  yes

Against the background of road safety, an algorithm is presented below that uses point clouds to make the most accurate prediction possible about the future position of pedestrians. A core element is to classify the current state of movement of pedestrians over a random forest. The focus is on early detection of changes between individual states. The classification is based on information about posture as a feature, which is obtained by analyzing the distance between the points of a cloud and the local planes it contains. The estimation of pedestrian position and dynamics using an Interacting Multiple Model Kalman Filter is the second core element. Finally, a prediction of the future position of a pedestrian is made using a combination of filter solution and classification. It is shown that the accuracy of this estimation exceeds the accuracy of a prediction based solely on the filter solution.