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Optimal control and inverse optimal control with continuous updating for human behavior modeling. / Petrosian, Ovanes; Inga, Jairo; Kuchkarov, Ildus; Flad, Michael; Hohmann, Sören.

In: IFAC-PapersOnLine, Vol. 53, No. 2, 2020, p. 6670-6677.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Petrosian, O, Inga, J, Kuchkarov, I, Flad, M & Hohmann, S 2020, 'Optimal control and inverse optimal control with continuous updating for human behavior modeling', IFAC-PapersOnLine, vol. 53, no. 2, pp. 6670-6677. https://doi.org/10.1016/j.ifacol.2020.12.089

APA

Petrosian, O., Inga, J., Kuchkarov, I., Flad, M., & Hohmann, S. (2020). Optimal control and inverse optimal control with continuous updating for human behavior modeling. IFAC-PapersOnLine, 53(2), 6670-6677. https://doi.org/10.1016/j.ifacol.2020.12.089

Vancouver

Petrosian O, Inga J, Kuchkarov I, Flad M, Hohmann S. Optimal control and inverse optimal control with continuous updating for human behavior modeling. IFAC-PapersOnLine. 2020;53(2):6670-6677. https://doi.org/10.1016/j.ifacol.2020.12.089

Author

Petrosian, Ovanes ; Inga, Jairo ; Kuchkarov, Ildus ; Flad, Michael ; Hohmann, Sören. / Optimal control and inverse optimal control with continuous updating for human behavior modeling. In: IFAC-PapersOnLine. 2020 ; Vol. 53, No. 2. pp. 6670-6677.

BibTeX

@article{8fd9eeb2750647529b1e9c778adb3f35,
title = "Optimal control and inverse optimal control with continuous updating for human behavior modeling",
abstract = "The theory of optimal control has received considerable attention to model motion behavior or decision making of humans. Most approaches are based on a fixed (or infinite) time horizon which implies that all information is available at the beginning of the time interval. Nevertheless, it is reasonable to believe that the human uses information defined by a continuously moving information horizon at each time instant and adapts accordingly. Therefore, in this paper, we propose an optimal feedback control approach based on the paradigm of continuous updating. The model parameters which define individual human behavior consist of the cost function parameters and the length of the information horizon, which can be identified via a corresponding inverse optimal control approach. We show the applicability of the approach with simulations of a potential application example of human behavior identification from the point of view of a driving assistance system.",
author = "Ovanes Petrosian and Jairo Inga and Ildus Kuchkarov and Michael Flad and S{\"o}ren Hohmann",
note = "Publisher Copyright: Copyright {\textcopyright} 2020 The Authors. This is an open access article under the CC BY-NC-ND license Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 21st IFAC World Congress 2020 ; Conference date: 12-07-2020 Through 17-07-2020",
year = "2020",
doi = "10.1016/j.ifacol.2020.12.089",
language = "English",
volume = "53",
pages = "6670--6677",
journal = "IFAC-PapersOnLine",
issn = "2405-8963",
publisher = "Elsevier",
number = "2",

}

RIS

TY - JOUR

T1 - Optimal control and inverse optimal control with continuous updating for human behavior modeling

AU - Petrosian, Ovanes

AU - Inga, Jairo

AU - Kuchkarov, Ildus

AU - Flad, Michael

AU - Hohmann, Sören

N1 - Publisher Copyright: Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - The theory of optimal control has received considerable attention to model motion behavior or decision making of humans. Most approaches are based on a fixed (or infinite) time horizon which implies that all information is available at the beginning of the time interval. Nevertheless, it is reasonable to believe that the human uses information defined by a continuously moving information horizon at each time instant and adapts accordingly. Therefore, in this paper, we propose an optimal feedback control approach based on the paradigm of continuous updating. The model parameters which define individual human behavior consist of the cost function parameters and the length of the information horizon, which can be identified via a corresponding inverse optimal control approach. We show the applicability of the approach with simulations of a potential application example of human behavior identification from the point of view of a driving assistance system.

AB - The theory of optimal control has received considerable attention to model motion behavior or decision making of humans. Most approaches are based on a fixed (or infinite) time horizon which implies that all information is available at the beginning of the time interval. Nevertheless, it is reasonable to believe that the human uses information defined by a continuously moving information horizon at each time instant and adapts accordingly. Therefore, in this paper, we propose an optimal feedback control approach based on the paradigm of continuous updating. The model parameters which define individual human behavior consist of the cost function parameters and the length of the information horizon, which can be identified via a corresponding inverse optimal control approach. We show the applicability of the approach with simulations of a potential application example of human behavior identification from the point of view of a driving assistance system.

UR - http://www.scopus.com/inward/record.url?scp=85105078368&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2020.12.089

DO - 10.1016/j.ifacol.2020.12.089

M3 - Conference article

AN - SCOPUS:85105078368

VL - 53

SP - 6670

EP - 6677

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 2

T2 - 21st IFAC World Congress 2020

Y2 - 12 July 2020 through 17 July 2020

ER -

ID: 76866099