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Authors: Stefan Kerscher 1 ; Norbert Balbierer 1 ; Sebastian Kraust 1 ; Andreas Hartmannsgruber 1 ; Nikolaus Müller 2 and Bernd Ludwig 3

Affiliations: 1 Continental AG, Germany ; 2 Deggendorf Institute of Technology, Germany ; 3 University Regensburg, Germany

Keyword(s): Prediction, Path Planning, Uncertainty Estimation, Autonomous Driving, Kalman Filter.

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 struc tured environments. (More)

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Paper citation in several formats:
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 - VEHITS; ISBN 978-989-758-293-6; ISSN 2184-495X, SciTePress, pages 307-314. DOI: 10.5220/0006679103070314

@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 - VEHITS},
year={2018},
pages={307-314},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006679103070314},
isbn={978-989-758-293-6},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Intention-based Prediction for Pedestrians and Vehicles in Unstructured Environments
SN - 978-989-758-293-6
IS - 2184-495X
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
PB - SciTePress

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