Model predictive driving simulator motion cueing algorithm with actuator-based constraints

Garrett, Nikhil J.I.; Best, Matt C.

doi:10.1080/00423114.2013.783219

Cited by 50 publications

(19 citation statements)

References 10 publications

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“…The driven attributes evaluation relies on the subjective evaluation of vehicle motion, and therefore the motion cueing algorithm must be carefully chosen. The model predictive control (MPC) algorithm has been shown to have good performance and to be preferred by drivers [24][25][26], and therefore a version of this algorithm was used for this study [23]. The longitudinal and lateral accelerations in the simulator were generated through transient linear motions of the hexapod and sliding rails and the sustained acceleration of tilt coordination.…”

Section: Motion Cueing Algorithmmentioning

confidence: 99%

Evaluation of Vehicle Ride Height Adjustments Using a Driving Simulator

et al. 2020

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Testing of vehicle design properties by car manufacturers is primarily performed on-road and is resource-intensive, involving costly physical prototypes and large time durations between evaluations of alternative designs. In this paper, the applicability of driving simulators for the virtual assessment of ride, steering and handling qualities was studied by manipulating vehicle air suspension ride height (RH) (ground clearance) and simulator motion platform (MP) workspace size. The evaluation was carried out on a high-friction normal road, routinely used for testing vehicle prototypes, modelled in a driving simulator, and using professional drivers. The results showed the differences between the RHs were subjectively distinguishable by the drivers in many of the vehicle attributes. Drivers found standard and low RHs more appropriate for the vehicle in terms of the steering and handling qualities, where their performance was deteriorated, such that the steering control effort was the highest in low RH. This indicated inconsistency between subjective preferences and objective performance and the need for alternative performance metrics to be defined for expert drivers. Moreover, an improvement in drivers’ performance was observed, with a reduction of steering control effort, in larger MP configurations.

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Section: Motion Cueing Algorithmmentioning

confidence: 99%

Evaluation of Vehicle Ride Height Adjustments Using a Driving Simulator

et al. 2020

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“…Each actuator length is constrained between maximum and minimum values. Going into details, the inverse kinematic of the platform is derived by using a standard approach for hexapods [7], that is then extended to the complete mechanical structure. With reference to Fig.…”

Section: B Constraintsmentioning

confidence: 99%

“…A further improvement has been presented in [6] by introducing a more accurate prediction step, exploiting the repetitive pattern typical of the racing context, together with a decimation strategy to ease the computational burden. A recent work deals with the problem of exploiting the inverse kinematic model of an hexapod, still adopting linear models [7].…”

Section: Introductionmentioning

confidence: 99%

A non-linear MPC based Motion Cueing implementation for a 9 DOFs dynamic simulator platform

Bruschetta

Maran

Beghi

2014

53rd IEEE Conference on Decision and Control

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The use of dynamical driving simulators is nowadays common practice in many different application fields, such as driver training, vehicle development, and medical studies. Platforms with different mechanical structure are designed, depending on the particular application and the corresponding targeted market. The effectiveness of such devices is related to their capabilities of well reproducing the driving feelings, hence it is crucial that the motion control strategies generate both realistic and feasible signals to the platform, to assure that it is kept within its limited operation space. Such strategies are called Motion Cueing Algorithms (MCAs), and they are clearly tailored to the particular mechanical structure of the device. In this paper we describe an MCA based on non linear Model Predictive Control (NMPC) techniques for a simulator of new conception, that consists of an hexapod over a flat base moved by a tripod, thus exhibiting highly non linear behaviour. The procedure is based on previous works where a linear, MPCbased MCA has been applied to a simpler device. The algorithm has been evaluated on a simulation environment, and a first implementation on the real device is in progress. Preliminary results show that a full exploitation of the working area is achieved, while managing at best all the limitations given by the particular structure and preserving the ease of tune and intuitiveness of the linear approach.

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“…A parallel manipulator with 6 DOF, called Gough-Stewart platform, is used as a basic mechanism for advanced motion simulators. A driving simulator can be used to replicate situations, which are dangerous for human, and to study the influence of the driver fatigue on his reactions (Garrett and Best, 2013;Lozia, 2008).…”

Section: Introductionmentioning

confidence: 99%

Motion Planning of a Novel 2-DOF Parallel Manipulator Applied as Driving Simulator of the Wheel Loader

Knapczyk¹,

Tora²

2014

International Journal of Applied Mechanics and Engineering

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A novel parallel manipulator with 3 legs (2 actuated by linear actuators and one supporting pillar),which is applied in a wheel loader driving simulator, is proposed in this paper. The roll angle and the pitch angle of the platform are derived in closed-form of functions of the variable lengths of two actuators. The linear velocity and acceleration of the selected point and angular velocity of the moving platform are determined and compared with measurement results obtained in the respective point and in the body of the wheel loader. The differences between the desired and actual actuator displacements are used as feedback to compute how much force to send to the actuators as some function of the servo error. A numerical example with a proposed mechanism as a driving simulator is presented.

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Model predictive driving simulator motion cueing algorithm with actuator-based constraints

Cited by 50 publications

References 10 publications

Evaluation of Vehicle Ride Height Adjustments Using a Driving Simulator

Evaluation of Vehicle Ride Height Adjustments Using a Driving Simulator

A non-linear MPC based Motion Cueing implementation for a 9 DOFs dynamic simulator platform

Motion Planning of a Novel 2-DOF Parallel Manipulator Applied as Driving Simulator of the Wheel Loader

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