Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Inverse Optimal Control with Continuous Updating for a Steering Behavior Model with Reference Trajectory. / Kuchkarov, Ildus; Mitiai, German; Petrosian, Ovanes; Lepikhin, Timur; Inga, Jairo; Hohmann, Sören.
Mathematical Optimization Theory and Operations Research: Recent Trends - 20th International Conference, MOTOR 2021, Revised Selected Papers. ed. / Alexander Strekalovsky; Yury Kochetov; Tatiana Gruzdeva; Andrei Orlov. Springer Nature, 2021. p. 387-402 (Communications in Computer and Information Science; Vol. 1476 CCIS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Inverse Optimal Control with Continuous Updating for a Steering Behavior Model with Reference Trajectory
AU - Kuchkarov, Ildus
AU - Mitiai, German
AU - Petrosian, Ovanes
AU - Lepikhin, Timur
AU - Inga, Jairo
AU - Hohmann, Sören
N1 - Publisher Copyright: © 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Most real control processes continuously evolve in time and a participant may not have all the information about the process at the time of its initiation. For example, a driver only has local information about the curvature of a road or any obstacles that might necessitate a lane change. The continuous updating approach allows us to arrive at models accounting for the limited information available to subjects during the decision making process. Previously, authors have considered many variations and methods for applying the continuous information updating approach: optimality conditions for equilibrium and cooperative strategies were constructed for the linear-quadratic case [18, 20], the Hamilton-Jacobi-Belman equation [29, 30], Pontryagin’s maximum principle [31, 43]. Also an application of the continuous updating approach was introduced for the general inverse optimal control problem with continuous updating in the paper [27], where the continuous updating was used for identifying cost function parameters from measured data and also the value of the information horizon. In this paper, we apply a continuous updating approach to a special and practical case of an inverse optimal control problem of determining the behavior of a driver while driving along a reference trajectory. Here the inverse optimal control problem becomes nonautonomous since the reference trajectory is included in the objective function of the driver as a function of time. The real motion data from the steering wheel driving simulator is used and the conclusion is drawn.
AB - Most real control processes continuously evolve in time and a participant may not have all the information about the process at the time of its initiation. For example, a driver only has local information about the curvature of a road or any obstacles that might necessitate a lane change. The continuous updating approach allows us to arrive at models accounting for the limited information available to subjects during the decision making process. Previously, authors have considered many variations and methods for applying the continuous information updating approach: optimality conditions for equilibrium and cooperative strategies were constructed for the linear-quadratic case [18, 20], the Hamilton-Jacobi-Belman equation [29, 30], Pontryagin’s maximum principle [31, 43]. Also an application of the continuous updating approach was introduced for the general inverse optimal control problem with continuous updating in the paper [27], where the continuous updating was used for identifying cost function parameters from measured data and also the value of the information horizon. In this paper, we apply a continuous updating approach to a special and practical case of an inverse optimal control problem of determining the behavior of a driver while driving along a reference trajectory. Here the inverse optimal control problem becomes nonautonomous since the reference trajectory is included in the objective function of the driver as a function of time. The real motion data from the steering wheel driving simulator is used and the conclusion is drawn.
KW - Continuous updating
KW - Inverse optimal control
KW - Optimal control
UR - http://www.scopus.com/inward/record.url?scp=85115857093&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/80b4fa3e-d72b-3da5-961f-b6fe45b07289/
U2 - 10.1007/978-3-030-86433-0_27
DO - 10.1007/978-3-030-86433-0_27
M3 - Conference contribution
AN - SCOPUS:85115857093
SN - 9783030864323
T3 - Communications in Computer and Information Science
SP - 387
EP - 402
BT - Mathematical Optimization Theory and Operations Research
A2 - Strekalovsky, Alexander
A2 - Kochetov, Yury
A2 - Gruzdeva, Tatiana
A2 - Orlov, Andrei
PB - Springer Nature
T2 - 20th International Conference on Mathematical Optimization Theory and Operations Research , MOTOR 2021
Y2 - 5 July 2021 through 10 July 2021
ER -
ID: 86416324