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ThinkMind // International Journal On Advances in Systems and Measurements, volume 13, numbers 3 and 4, 2020 // View article sysmea_v13_n34_2020_2


Design and Objective Evaluation of Filter- and Optimization-based Motion Cueing Strategies for a Hybrid Kinematics Driving Simulator with 5 Degrees of Freedom

Authors:
Patrick Biemelt
Sandra Gausemeier
Ansgar Trächtler

Keywords: Interactive Driving Simulation; Motion Cueing; Washout Algorithm; Model Predictive Control; Objective Quality Criteria

Abstract:
Dynamic driving simulators have become a key technology to support the development and optimization process of modern vehicle systems both in academic research and in the automotive industry. However, the validity of the results obtained in simulator tests depends significantly on the adequate reproduction of the simulated vehicle movements and the associated immersion of the driver. Therefore, specific motion platform control strategies, so-called Motion Cueing Algorithms (MCA), are used to render the acting accelerations and angular velocities within the physical limitations of the driving simulator best possible. In this paper, we describe the design and implementation of two different control approaches for this task, using a simulator with hybrid kinematics motion system as an application example. Motivated by its unique features, an improved filter-based algorithm as well as a real-time capable optimization-based strategy following the idea of Model Predictive Control (MPC) are presented and discussed in detail. By means of introduced quality criteria, both algorithms are objectively compared with regard to various standard driving scenarios. These include longitudinal and lateral dynamic maneuvers to estimate the overall improvements of each MCA for interactive driving simulation. Measurement data indicate that both approaches yield an adequate control quality, however, the MPC-based algorithm better handles the kinematic constraints of the simulator due to the integration of additional model knowledge.

Pages: 203 to 219

Copyright: Copyright (c) to authors, 2020. Used with permission.

Publication date: December 30, 2020

Published in: journal

ISSN: 1942-261x

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