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Authors: Henrik Bey 1 ; Maximilian Tratz 1 ; Moritz Sackmann 1 ; Alexander Lange 2 and Jörn Thielecke 1

Affiliations: 1 Institute of Information Technology, FAU Erlangen-Nürnberg, 91058 Erlangen, Germany ; 2 Pre-development of Automated Driving, AUDI AG, 85045 Ingolstadt, Germany

Keyword(s): Automated Driving, Decision Making under Uncertainty, POMDP.

Abstract: Behavior planning of automated vehicles entails many uncertainties. Partially Observable Markov Decision Processes (POMDP) are a mathematical framework suited for formulating the arising sequential decision problems. Solving POMDPs used to be intractable except for overly simplified examples, especially when execution time is of importance. Recent sampling-based solvers alleviated this problem by searching not for the exact but rather an approximated solution, and made POMDPs usable for many real-world applications. One of these algorithms is the Adaptive Belief Tree (ABT) algorithm which will be analyzed in this work. The scenario under consideration is an uncertain obstacle in the way of an automated vehicle. Following this example, the setup of POMDP and ABT is derived and the impact of important parameters is assessed in simulation. As such, this work provides a hands-on tutorial, giving insights and hints on how to overcome the pitfalls in using sampling-based POMDP solvers.

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Paper citation in several formats:
Bey, H.; Tratz, M.; Sackmann, M.; Lange, A. and Thielecke, J. (2020). Tutorial on Sampling-based POMDP-planning for Automated Driving. In Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-419-0; ISSN 2184-495X, SciTePress, pages 312-321. DOI: 10.5220/0009344703120321

@conference{vehits20,
author={Henrik Bey. and Maximilian Tratz. and Moritz Sackmann. and Alexander Lange. and Jörn Thielecke.},
title={Tutorial on Sampling-based POMDP-planning for Automated Driving},
booktitle={Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2020},
pages={312-321},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009344703120321},
isbn={978-989-758-419-0},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Tutorial on Sampling-based POMDP-planning for Automated Driving
SN - 978-989-758-419-0
IS - 2184-495X
AU - Bey, H.
AU - Tratz, M.
AU - Sackmann, M.
AU - Lange, A.
AU - Thielecke, J.
PY - 2020
SP - 312
EP - 321
DO - 10.5220/0009344703120321
PB - SciTePress

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