Motion Cueing Algorithm Research Articles

The influence of yaw motion on the perception of active vs passive visual curvilinear displacement.

Self-motion perception, which partly determines the realism of dynamic driving simulators, is based on multisensory integration. However, it remains unclear how the brain integrates these cues to create adequate motion perception, especially for curvilinear displacements. In the present study, the effect of visual, inertial and visuo-inertial cues (concordant or discordant bimodal cues) on self-motion perception was analyzed. Subjects were asked to evaluate (externally produced) or produce (self-controlled) curvilinear displacements as accurately as possible. The results show systematic overestimation of displacement, with better performance for active subjects than for passive ones. Furthermore, it was demonstrated that participants used unimodal or bimodal cues differently in performing their activity. When passive, subjects systematically integrated visual and inertial cues even when discordant, but with weightings that depended on the dynamics. On the contrary, active subjects were able to reject the inertial cue when the discordance became too high, producing self-motion perception on the basis of more reliable information. Thereby, multisensory integration seems to follow a non-linear integration model of, i.e., the cues' weight changes with the cue reliability and/or the intensity of the stimuli, as reported by previous studies. These results represent a basis for the adaptation of motion cueing algorithms are developed for dynamic driving simulators, by taking into account the dynamics of simulated motion in line with the status of the participants (driver or passenger).

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching the motion limitations.

New motion cueing algorithm for driving simulator based on variant harmonic wavelet

As one of key technologies in movement perception simulation, motion cueing algorithm (MCA) is usually used for exploiting driving simulator within limited workspace and bounded dynamic characteristics. Several MCAs are investigated for movement perception simulation, however, the classical washout algorithm has shortage in time delay, the optimal washout algorithm completely depends on accurate vestibular model, while the adaptive washout algorithm needs long computational time. So the result of these defects is to reduce driving simulation fidelity. In order to meet the performances of high fidelity and real-time for driving simulator, this paper proposes a novel hybrid coordination motion cueing algorithm based on variant harmonic wavelet. The variant harmonic wavelet, mutating from traditional harmonic wavelet, has only three special wavelets. For its outstanding performances, box-shaped filter characteristics and zero phase shift, it would enhance driving sensation fidelity and real-time. Meanwhile, hybrid tilt and over-tilt coordination mechanism are introduced to design the new MCA for providing a special coordination strategy. Finally, the effectiveness and superiority of the new MCA are validated by simulation.

Prepositioning of driving simulator motion systems

Motion base driving simulators have limited space in which to recreate the motions of the simulated road vehicle. Conventional motion cueing algorithms strive to centre the cabin in the simulator motion envelope to accommodate accelerations in a worst case scenario while respecting the physical boundaries. Using information about the road ahead one can preposition the cabin to an off-centre point, virtually increasing the available space so that larger motions are made possible. The prepositioning algorithm presented here was developed as an addition to a classical motion cueing algorithm and makes use of road data and vehicle speed to adjust the simulator displacement. Simulations show that the amount of acceleration presented by an x, y-sled system can, with prepositioning, be increased by up to 25% in longitudinal and 53% in lateral direction for an example road. A comparative study including 12 test subjects indicates that the perceived realism is rated higher with prepositioning.

Optimal Race Car Motion Cueing

This paper explores the application of numerical optimal control (NOC) to the synthesis of motion cueing algorithms for race-car simulators. These techniques are used to design washout filters that address the limitations of the commonly-employed linear quadratic Guassian (LQG) regulator and classical frequency shaping strategies. The primary disadvantage of the LQG and classical tuning methods is that they do not recognise explicitly the hardware limitations of the platform and thus have to rely on an iterative process to address workspace limitations. In two new algorithms a kinematic model of the platform is used to constrain explicitly the platform's motion within the available workspace. The first algorithm is directed to the optimisation of the parameters of a linear washout filter, while in the second approach the platform motion is governed by an open-loop optimal control. The results of the two new algorithms are tested on race-car minimum lap-time simulations, and then compared with a linear-optimal-control based solution. The race-car scenario presents different challenges from the passenger car and aircraft contexts; these differences are discussed.

Motion Scaling for High-Performance Driving Simulators

Advanced driving simulators aim at rendering the motion of a vehicle with maximum fidelity, which requires increased mechanical travel, size, and cost of the system. Motion cueing algorithms reduce the motion envelope by taking advantage of limitations in human motion perception, and the most commonly employed method is just to scale down the physical motion. However, little is known on the effects of motion scaling on motion perception and on actual driving performance. This paper presents the results of a European collaborative project, which explored different motion scale factors in a slalom driving task. Three state-of-the-art simulator systems were used, which were capable of generating displacements of several meters. The results of four comparable driving experiments, which were obtained with a total of 65 participants, indicate a preference for motion scale factors below 1, within a wide range of acceptable values (0.4-0.75). Very reduced or absent motion cues significantly degrade driving performance. Applications of this research are discussed for the design of motion systems and cueing algorithms for driving simulation.

Optimal and Coherence Zone Comparison Within and Between Flight Simulators

In flight simulation, motion-cueing algorithms are used to transform aircraft motion into motion within the simulator limits. When looking for the best match between visual and inertial amplitude in a simulator, researchers have found that there is a range of inertial amplitudes, rather than a single inertial value, that is perceived by subjects as optimal. This zone, hereafter referred to as the optimal zone, seems to correlate to the perceptual coherence zones measured in flight simulators. However, no studies were found in which these two zones were compared. This study investigates the relation between the optimal and the coherence-zone measurements within and between different simulators. An experiment was conducted at NASA Langley Research Center, where two simulators were used to measure the optimal and the coherence zone in the sway axis. Results show that the optimal zone lies within the coherence zone. The center of the optimal zone is significantly lower than the center of the coherence zone. In addition, it was found that, whereas the width of the coherence zone depends on the visual amplitude and frequency, the width of the optimal zone remains constant. No statistical differences between the two simulators were found.

Evaluation of a new body-sideslip-based driving simulator motion cueing algorithm

This paper describes a new motion cueing algorithm for motion-based driving simulators. The algorithm uses the simulated vehicle’s body sideslip angle as the demand for the motion platform’s yaw degree of freedom. The current state of the art for motion cueing algorithms involves some form of filter or controller that limits the bandwidth of the vehicle motion before using this as the motion platform demand; the algorithm is tuned such that the platform does not exceed its limits. However, this means that information about the vehicle state that is contained within the motion is removed indiscriminately. Since the body sideslip angle will fit within the platform yaw limit under normal conditions, it does not need to be filtered beforehand, and thus no information must be removed. The implementation of the body-sideslip-based algorithm is described, as is a set of tests using human participants wherein the body sideslip algorithm was compared against the three most popular existing algorithms (namely the classical, adaptive and linear quadratic regulator algorithms) for normal road driving. The results of these tests indicate that the body sideslip algorithm performs as well as, or marginally better than, the other algorithms; future work will test the algorithm under limit handling conditions, to see whether the approach of preserving vehicle state information improves the simulator driver’s perception.

Roll rate thresholds in driving simulation

The restricted operational space of dynamic driving simulators requires the implementation of motion cueing algorithms that tilt the simulator cabin to reproduce sustained accelerations. In order to avoid conflicting inertial cues, the tilt rate is limited below drivers’ perceptual thresholds, which are typically derived from the results of classical vestibular research, where additional sensory cues to self-motion are removed. These limits might be too conservative for an ecological driving simulation, which provides a variety of complex visual and vestibular cues as well as demands of attention which vary with task difficulty. We measured roll rate detection threshold in active driving simulation, where visual and vestibular stimuli are provided as well as increased cognitive load from the driving task. Here thresholds during active driving are compared with tilt rate detection thresholds found in the literature (passive thresholds) to assess the effect of the driving task. In a second experiment, these thresholds (active versus passive) are related to driving preferences in a slalom driving course in order to determine which roll rate values are most appropriate for driving simulators so as to present the most realistic driving experience. The results show that detection threshold for roll in an active driving task is significantly higher than the limits currently used in motion cueing algorithms, suggesting that higher tilt limits can be successfully implemented to better optimize simulator operational space. Supra-threshold roll rates in the slalom task are also rated as more realistic. Overall, our findings indicate that increasing task complexity in driving simulation can decrease motion sensitivity allowing for further expansion of the virtual workspace environment.

Motion Cueing Algorithm Online Parameter Switching in a Blink of an Eye—A Time-Variant Approach

Abstract The development and evaluation of human centered driver assistance systems is one major research focus within the automotive domain of the Institute of Transportation Systems (TS) at the German Aerospace Center (DLR). To investigate the impact of new driver assistance systems on driver behavior different research facilities from simulations to real car environments are used. One research facility at TS is the dynamic driving simulator with a hexapod structure. Using dynamic driving simulators to reproduce real car motion is a major challenge as the workspace is limited. Within this paper a method of state adaption is presented. This method enables a discrete switching of high-pass filter corner frequencies within one single simulation time step. Thereby discontinuities of the filter output signal as well as in the derivatives of the output signal are avoidable. Thus, it is possible to adapt corner frequencies of high-pass filters of a Motion Cueing Algorithm (MCA), according to the current driving situation. The paper starts with a description of the MCA currently used for the motion rendering at TS. Afterward the state adaption method is described including the challenges for adapting this method to the current MCA structure. In the end of the new structure for the time-variant MCA as well as the boundary conditions for corner frequency switching and the test results of the new time-variant approach using the state adaption method are outlined.

An Optimal Washout Filter Design with Fuzzy Compensation for a Motion Platform

AbstractThe realistic motion of the vehicular simulator is produced by the motion cueing algorithm. An optimal washout filter, taking into account the limitation of the simulator's workspace, is applied here to minimize human's perception error in order to provide realistic behavior. The filtering algorithm compares the human's perception of driving simulator with that driving actual vehicle obtained based on the human vestibular model. The cost function accounting for both the pilot's sensation error and the range of platform motion is minimized to achieve more realistic motion and efficient usage of the limited workspace. To compensate the drawback of fixed parameters in optimal washout filter, the fuzzy control rules of motion perception are applied to online adjust the filtered signals. The simulation results verify the efficient utilization of platform workspace and less sensation error compared with that obtained by the classical washout filter.

A Robotic System with a Hybrid Motion Cueing Controller for Inertia Tensor Approximation in Micro-Manipulations

This paper summarizes the development of a robotic system for the approximation of inertia tensor of micro-sized rigid bodies. We described the design and computer-based simulation of a 6-DOF motion platform in our earlier work [ 32 ] that benefits from an anthropological serial manipulator design. In [ 32 ] we emphasized that, in contrast to a standard configuration based on linear actuators, a mechanism with actuator design inspired from an anthropological kinematic structure offers relatively a larger motion envelope and higher dexterity making it a viable motion platform for micromanipulations. After having described the basic design and kinematic analysis of our motion platform in [ 32 ], we now aim to propose an advanced motion cueing algorithm for facilitating the identification of inertial parameters at micron-level. The motion cueing algorithm for achieving high fidelity dynamic simulation is described in this paper using a hybrid force-position-based controller. The inertia tensor identification is done by generating a controlled motion on the specimen and measuring the resultant forces and moments to approximate the inertia tensor using rigid body dynamics equations. The paper evaluates the performance of the controller using closed-loop dynamic simulations and validates the significance of the proposed method through experimental results.

Simulating believable forward accelerations on a stewart motion platform

It is still an unsolved problem how to optimally simulate self-motion using motion simulators. We investigated how a forward acceleration can be simulated as believably as possible on a hexapod motion platform equipped with a projection screen. Human participants rated the believability of brief forward accelerations. These were simulated as visual forward accelerations over a ground plane with people as size cues, presented together with brief forward surge translations and backward pitches of the platform, and synchronous random up--down movements of the camera in the visual scene and the platform. The magnitudes of all of the parameters were varied independently across trials. Even though variability between participants was high, the most believable simulation occurred when visual accelerations were combined with backward pitches of the platform, which changed the gravitoinertial vector direction approximately consistent with the visual acceleration. However, a wide range of platform pitches was accepted as believable. With high visual acceleration cues most participants reported trials as realistic even when the platform tilt rate was above vestibular canal thresholds reported in other works. Other manipulated parameters had only a mild influence on the responses. These results can be used to optimize motion-cueing algorithms for simulating linear accelerations in motion simulators.

Comparison of Three Motion Cueing Algorithms for Curve Driving in an Urban Environment

Research on new automotive systems currently relies on car driving simulators, as they are a cheaper, faster, and safer alternative to tests on real tracks. However, there is increasing concern about the motion cues provided in the simulator and their influence on the validity of these studies. Especially for curve driving, providing large sustained acceleration is difficult in the limited motion space of simulators. Recently built simulators, such as Desdemona, offer a large motion space showing great potential as automotive simulators. The goal of this research is: first, to develop a motion drive algorithm for urban curve driving in the Desdemona simulator; and second, to evaluate the solution through a simulator driving experiment. The developed algorithm, the one-to-one yaw algorithm, is compared to a classical washout algorithm (adapted to the Desdemona motion space) and a control condition where only road rumble is provided. Results show that regarding lateral motion, the absence of cues in the rumble condition is preferred over the presence of false cues in the classical algorithm. “No motion” seems to be favored over “bad motion.” In terms of longitudinal motion, the one-to-one yaw and the classical algorithm are voted better than the rumble condition, showing that the addition of motion cues is beneficial to the simulation of braking. In a general way, the one-to-one yaw algorithm is classified better than the other two algorithms.

Optimal motion cueing for 5-DOF motion simulations via a 3-DOF motion simulator

This study presents a novel motion-cueing strategy, which is applied to a motion simulator with three rotational degrees of freedom (DOF) to perform the roll, pitch, yaw, surge, and sway motions by using an online optimization algorithm. The weighting functions are adaptively tuned in each step, and the optimal Euler angles are obtained analytically. This motion-cueing algorithm is efficient since it requires no recursive search on the optimal solution. Experiments demonstrating the validity of the 5-DOF motion simulation are also included.

Integrated Design of the Motion Cueing System for a Wright Flyer Simulator

Given a specific flight vehicle and a flying task—in this case, the 1903 Wright Flyer—a forward design process can be utilized to specify a corresponding flight simulator motion cueing system. This process, presented in this paper, is based on the analysis of the pilot‐vehicle control loop by using a pilot model incorporating both visual and vestibular feedback and the aircraft dynamics. After substituting the pilot model to control the simulated aircraft, the analysis tools are used to adjust the washout filter parameters with the goal of maintaining the original pilot control behavior as much as possible. This process allows the objective specification of the motion cueing algorithm. Then, based on flight files representative of the operational flight envelope the required motion system work space is determined. The motion-base geometry is established based on practical limitations, as well as criteria for the stability of the platform with respect to singular conditions. With this process the characteristics of the aircraft, the tasks to be simulated, and the missions themselves are taken into account in defining the simulator motion cueing system.

Integrated design of flight simulator motion cueing systems

AbstractAn advanced design process applicable to the specification of flight simulator cueing systems is presented in this paper. This process is based on the analysis of the pilot-vehicle control loop by using a pilot model incorporating both visual and vestibular feedback, and the aircraft dynamics. After substituting the model for the simulated aircraft, the analysis tools are used to adjust the washout filter parameters with the goal of restoring pilot control behaviour. This process allows the specification of the motion cueing algorithm. Then, based on flight files representative of the operational flight envelope, the required motion system space is determined. The motion-base geometry is established based on practical limitations, as well as criteria for the stability of the platform with respect to singular conditions. With this process the characteristics of the aircraft, the tasks to be simulated, and the missions themselves are taken into account in defining the simulator motion cueing system.

Optimal Motion Cueing Algorithm Using the Human Body Model.

This paper introduces the development of a motion cueing algorithm which produces motion cues from vehicle motion signals. The simulator, a parallel manipulator, has the limitation on the workspace. In order to overcome this problem, the motion cueing algorithm is needed. Here, we suggest a new optimal motion cueing algorithm where the human body model (ISO 2631-1) as well as the human perception model are incorporated. And we show the performance of this algorithm using the computer simulation. In simulation, we produce motion cues from vehicle motion signals through the proposed algorithm and show sensation errors which the human feel between vehicle signals and the simulator motions subjected to motion cues.