Intention-based Prediction for Pedestrians and Vehicles in Unstructured Environments

Stefan Kerscher, Norbert Balbierer, Sebastian Kraust, Andreas Hartmannsgruber, Nikolaus Müller, Bernd Ludwig

Abstract

Motion prediction for holonomic objects in unstructured environments is an ambitious task due to their high freedom of movement compared with non-holonomic objects. In this paper, we present a method for inferring the future goal of holonomic objects by a heuristic generation of target points (tp) and following discriminating decision making. The target points are generated, in a manner that covers the most common motion hypotheses like following or staying, safety relevant motion hypotheses like crossing future ego trajectories or the movement to special points of interest, e.g. gained from a map. Subsequently, for each considered object a trajectory to the inferred target point will be planned. Finally, the uncertainty of the trajectory is estimated by applying a Kalman Filter with a dynamically adjusted process noise matrix. An additional benefit of this concept is its ability to cope with a different quality of context knowledge, so it can produce sound results even at poor structured environments.

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Paper Citation


in Harvard Style

Kerscher S., Balbierer N., Kraust S., Hartmannsgruber A., Müller N. and Ludwig B. (2018). Intention-based Prediction for Pedestrians and Vehicles in Unstructured Environments.In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-293-6, pages 307-314. DOI: 10.5220/0006679103070314


in Bibtex Style

@conference{vehits18,
author={Stefan Kerscher and Norbert Balbierer and Sebastian Kraust and Andreas Hartmannsgruber and Nikolaus Müller and Bernd Ludwig},
title={Intention-based Prediction for Pedestrians and Vehicles in Unstructured Environments},
booktitle={Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2018},
pages={307-314},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006679103070314},
isbn={978-989-758-293-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Intention-based Prediction for Pedestrians and Vehicles in Unstructured Environments
SN - 978-989-758-293-6
AU - Kerscher S.
AU - Balbierer N.
AU - Kraust S.
AU - Hartmannsgruber A.
AU - Müller N.
AU - Ludwig B.
PY - 2018
SP - 307
EP - 314
DO - 10.5220/0006679103070314