Keen, SD and Cole, DJ (2012) Bias-free identification of a linear model-predictive steering controller from measured driver steering behavior. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42. pp. 434-443. ISSN 1083-4419Full text not available from this repository.
Recent developments in modeling driver steering control with preview are reviewed. While some validation with experimental data has been presented, the rigorous application of formal system identification methods has not yet been attempted. This paper describes a steering controller based on linear model-predictive control. An indirect identification method that minimizes steering angle prediction error is developed. Special attention is given to filtering the prediction error so as to avoid identification bias that arises from the closed-loop operation of the driver-vehicle system. The identification procedure is applied to data collected from 14 test drivers performing double lane change maneuvers in an instrumented vehicle. It is found that the identification procedure successfully finds parameter values for the model that give small prediction errors. The procedure is also able to distinguish between the different steering strategies adopted by the test drivers. © 2006 IEEE.
|Uncontrolled Keywords:||Driver modelling model predictive control nonlinear system identification|
|Divisions:||Div C > Applied Mechanics|
|Depositing User:||Cron job|
|Date Deposited:||04 Feb 2015 22:18|
|Last Modified:||05 Feb 2015 07:32|