Intercepting real and simulated falling objects: What is the difference?

Baurès, Robin; Amorim, Michel-Ange; Hecht, Heiko

doi:10.1016/j.jneumeth.2009.07.022

Cited by 7 publications

(5 citation statements)

References 22 publications

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“…Although the participants overestimated the theoretical lean angles, these overestimations decreased with the increase in the theoretical lean angle. Such overestimations are consistent with studies comparing other real and virtual environment such as ball catching (e.g., Baurès et al, 2009) or distance perception (e.g., Plumert et al, 2005), presumably suggesting that motorcycle simulations may require amplifying the subjective experience of the curves.…”

Section: Discussionsupporting

confidence: 86%

Towards identifying the roll motion parameters of a motorcycle simulator

Shahar¹,

Dagonneau²,

Caro³

et al. 2014

Applied Ergonomics

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This study aimed at identifying the roll motion parameters of a motorcycle simulator prototype. Experienced motorcyclists tuned the angular physical movement of the mock-up and that of the visual scene to achieve an optimal riding experience during curves. The participants exceeded the rolling angles that would be required in real-world riding, while avoiding leaning the mock-up beyond 10°. In addition, they were more influenced by the speed of the virtual motorcycle than by road curvature, especially in a wide field of view. Heterogeneity was found in the roll applied to the visual scene. The overall patterns suggest that at least when washout is not applied to remove the side forces that in real-world riding are compensated by a centrifugal force, greater roll of the visual at the expense of the mock-up is mandatory to avoid performance biases that might be enhanced due to fear of falling off the simulator. Future roll motion models must take into consideration factors such as riding postures, which might not only influence the forces operating on the rider-motorcycle system, but also how motorcyclists perceive the visual world.

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Section: Discussionsupporting

confidence: 86%

Towards identifying the roll motion parameters of a motorcycle simulator

Shahar¹,

Dagonneau²,

Caro³

et al. 2014

Applied Ergonomics

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“…Second, in the moving target interception task, participants must capture a fast-moving object through a hand or another end-effector. Intercepting a moving target requires gross spatial movement of an end-effector (hand or foot) [4,9], which is outside the scope of temporal pointing. Also, interception is a very general idea that subsumes many instances [37]: pursuit, head-on, receding, and perpendicular.…”

Section: Studies Of Temporal Tasksmentioning

confidence: 99%

“…The stimulus is simply an impulse signal [12,27,31]. Some have studied stimuli with long durations, rather than impulse, but did not report or model users' error rate [4,27,38,40].…”

Section: Studies Of Temporal Tasksmentioning

confidence: 99%

“…We choose an opponent color pair (yellow-blue) to maximize the color contrast; a dark blue color (#000001) for the selection region and a moderate yellow color (#202000) for the moving target. 4 For input device, we directly connected the left button of a dummy mouse to the experiment driver board. The mouse button was activated with 55 cN force at 0.4 mm displacement.…”

Section: Parameter Explorationmentioning

confidence: 99%

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Moving Target Selection

Lee

Kim

Oulasvirta

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

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This paper investigates a common task requiring temporal precision: the selection of a rapidly moving target on display by invoking an input event when it is within some selection window. Previous work has explored the relationship between accuracy and precision in this task, but the role of visual cues available to users has remained unexplained. To expand modeling of timing performance to multimodal settings, common in gaming and music, our model builds on the principle of probabilistic cue integration. Maximum likelihood estimation (MLE) is used to model how different types of cues are integrated into a reliable estimate of the temporal task. The model deals with temporal structure (repetition, rhythm) and the perceivable movement of the target on display. It accurately predicts error rate in a range of realistic tasks. Applications include the optimization of difficulty in game-level design.

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“…However, the control of steering was seen to be more difficult, as revealed by a larger number of lane departures and a change in the trade-off between guiding and look-ahead fixations. Although researchers' interest in VR systems to study human movement control is relatively well established (e.g., Baurès, Benguigui, Amorim, & Hecht, 2009;Lepecq, Bringoux, Pergandi, Coyle, & Mestre, 2009;Zaal & Bootsma, 2011), our results confirm previous findings that show the influence of immersive and interactive characteristics of VR systems on how humans behave or perform (e.g., Lobjois et al, 2016b;Morice et al, 2008). Although a number of studies have paid attention to simulator characteristics to improve physical fidelity (e.g., Chatziastros, Wallis, & Bülthoff, 1999;Grechkin et al, 2014;Jamson & Jamson, 2010;Klüver, Herrigel, Heinrich, Schöner, & Hecht, 2016), it is acknowledged that behavioral validity is more important than physical validity (Klüver et al, 2016;Pinto et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

Effects of motorcycle simulator configurations on steering control and gaze behavior in bends.

Lobjois¹,

Mars²

2020

Journal of Experimental Psychology: Applied

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The recent development of motorcycle simulators has made it possible to study rider behavior in safe conditions. However, their use still raises validity issues. Our study examined how riders' steering and gaze behaviors and subjective experience are influenced by motorcycle roll tilt and reverse steering, which are considered to be essential factors in real-life motorcycle riding. The results revealed that tilting the motorcycle in the roll plane did not lead to significant changes in rider behavior, gaze sampling or perceived realism. The steering control strategy adopted by riders did, however, significantly influence these results. A direct steering control strategy meant that riders took a racing path and scanned the road far in advance. When reverse steering was implemented, however, riders chose to take a "safety path", as recommended by training manuals. Reverse steering also received the highest realism score. However, steering control was more difficult, as shown by the larger number of lane departures recorded and a change in the trade-off between guiding and look-ahead fixations. This suggests that although reverse steering matches riders' real control behavior and improves the subjective experience of simulator riding, it is hindered by an inadequate internal model of vehicle dynamics. Public Significance Statement Increasing physical fidelity of a motorcycle simulator led to improved subjective realism and riding behavior but impaired steering control underlying processes. These results provide an objective basis for researchers to select the type of simulator adapted to their research needs.

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Intercepting real and simulated falling objects: What is the difference?

Cited by 7 publications

References 22 publications

Towards identifying the roll motion parameters of a motorcycle simulator

Towards identifying the roll motion parameters of a motorcycle simulator

Moving Target Selection

Effects of motorcycle simulator configurations on steering control and gaze behavior in bends.

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