Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments

Tim Brudigam, Fulvio Di Luzio, Lucia Pallottino, Dirk Wollherr, Marion Leibold

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

14 Zitate (Scopus)

Abstract

Stochastic Model Predictive Control has proved to be an efficient method to plan trajectories in uncertain environments, e.g., for autonomous vehicles. Chance constraints ensure that the probability of collision is bounded by a predefined risk parameter. However, considering chance constraints in an optimization problem can be challenging and computationally demanding. In this paper, we present a grid-based Stochastic Model Predictive Control approach. This approach allows to determine a simple deterministic reformulation of the chance constraints and reduces the computational effort, while considering the stochastic nature of the environment. Within the proposed method, we first divide the environment into a grid and, for each predicted step, assign each cell a probability value, which represents the probability that this cell will be occupied by surrounding vehicles. Then, the probabilistic grid is transformed into a binary grid of admissible and inadmissible cells by applying a threshold, representing a risk parameter. Only cells with an occupancy probability lower than the threshold are admissible for the controlled vehicle. Given the admissible cells, a convex hull is generated, which can then be used for trajectory planning. Simulations of an autonomous driving highway scenario show the benefits of the proposed grid-based Stochastic Model Predictive Control method.

OriginalspracheEnglisch
Titel2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9781728141497
DOIs
PublikationsstatusVeröffentlicht - 20 Sept. 2020
Veranstaltung23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020 - Rhodes, Griechenland
Dauer: 20 Sept. 202023 Sept. 2020

Publikationsreihe

Name2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020

Konferenz

Konferenz23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020
Land/GebietGriechenland
OrtRhodes
Zeitraum20/09/2023/09/20

Fingerprint

Untersuchen Sie die Forschungsthemen von „Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren