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 -