This study presents a driving simulator experiment to evaluate three different motion cueing algorithms based on model predictive control. The difference among these motion strategies lies in the type of mathematical model used. The first one contains only the dynamic model of the platform, while the others integrate additionally two different vestibular system models. We compare these three strategies to discuss the tradeoffs when including a vestibular system model in the control loop from the user's viewpoint. The study is conducted in autonomous mode and in free driving mode, as both play an important role in motion cueing validation. A total of 38 individuals participated in the experiment; 19 drove the simulator in free driving mode and the remaining using the autonomous driving mode. For both driving modes, substantial differences is observed. The analysis shows that one of the vestibular system models is suitable for driving simulators, as it thoroughly restores high-frequency accelerations and is well noted by the participants, especially those in the free driving mode. Further tests are needed to analyze the advantages of integrating the chosen vestibular system model in the control design for motion cuieng algorithms. Regarding the autonomous mode, further research is needed to examine the influence of the vestibular system model on the motion performance, as the behavior of the autonomous model may implicitly interfere with subjective assessments.

As part of an evaluation process of user experience realism in a Virtual Reality (VR) system, we focus in this paper on one of the core characteristics of vision: the relationship between contrast and luminance. The experiment aims at validating in VR reaction time predictions given by Rea and Ouellette's model. The subjects have to distinguish, as fast as they can, a target object from an uniform background. Our results did not match the predictions of the model. Our subjects showed higher performance in performing the task than expected. At low level of contrast, our subjects could easily perceive a target they should not have been able to see at all. This is explained by the size of the visual field surrounding the target: at low level of visibility, the larger the surrounding, the easier perception the is. We conclude that the Rea and Ouellette's model could be applied in VR if a specific visual field size factor was added.

This paper deals with motion control for an 8-degree-of-freedom (DOF) high performance driving simulator. We formulate a constrained optimal control that defines the dynamical behavior of the system. Furthermore, the paper brings together various methodologies for addressing feasibility issues arising in implicit model predictive control-based motion cueing algorithms. The implementation of different techniques is described and discussed subsequently. Several simulations are carried out in the simulator platform. It is observed that the only technique that can provide ensured closed-loop stability by assuring feasibility over all prediction horizons is a braking law that basically saturates the control inputs in the constrained form.

In co-located collaborative environment for product design, new groupware of multi-view system allows multiple experts to have individual visual information. A co-located multi-view VR system and a multidisciplinary task have been created and studied. Results show that using multi-view VR system achieves a better effectiveness and user performance. Then, an application for collaborative ergonomic design is explored and an industrial multidisciplinary scenario is realized with proposed system.

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.

Many shading models are able to provide realistic rendering of lighting effects under various atmospheric conditions but computational times are often expensive. This paper proposes a method to render lighting effects within participating media in real-time on a graphics workstation. It consists of mathematical approximations based on a re-formulation of the light transport equation considering atmospheric scattering with light sources described by their luminous intensity distribution. Hardware capabilities of graphics computer boards are used to accelerate parts of the rendering process.