|Acquisition Program: ||Deployable Virtual Training Environment (DVTE),|| Objective: ||To develop and validate a tool that guides virtual environment training system designers and integrators in the selection of the multimodal technology and fidelity level required to support training requirements.
|| Description: ||Virtual Environment (VE) Systems are becoming more and more prevalent in training both military and nonmilitary related tasks. Virtual training systems can be an effective means to train tasks that could prove to be too dangerous or costly to train in the real world, such as military operations or complex medical procedures. Despite this, there is a lack of guidance on how to build environments that best support training specific tasks. This results in an ever-increasing challenge for training designers to navigate the selection of technology components to provide visual, auditory, and haptic sensory cues. Technology selection is nontrivial, as empirical evidence indicates that the fidelity of these multimodal sensory cues has a significant impact on trainee performance and transfer of training (Stanney, Samman, Reeves, Hale, Buff, Bowers, Goldiez, Nicholson, & Lackey, 2003). For example, the fidelity of visual display systems may range from desktop monitor systems to fully immerse, high resolution head-mounted display (HMD) systems, all with varying degrees of impact on training. The level of audio fidelity that is to be integrated into a system could vary from no audio to the use of complex individually measured head-related transfer functions (HRTF) models to present 3D audio. Research suggests that spatialized audio can impact the sense of presence in the virtual environment (Hendrix, 1996, Blauert, 1997). It has also been shown that the quality of auditory display can have an effect the perceived quality of visual displays (Storms, 1998). Inclusion of haptic interaction with a visual display has shown improved individual task performance for object interaction (Richard, Burdea, Gomez, & Coiffet, 1994) and wayfinding (Insko, Meehan, Whitton, & Brooks, 2001), as well as enhanced performance in a shared VE (Basdogan, Ho, Srinivasan, & Slater, 2000). Feygin, Keehner and Tendick (2002) showed that haptic guidance improved timing performance regardless of whether or not vision was available during task performance. Haptics may also increase the fidelity of a VE system, which can enhance training transfer (Swezey & Llaneras, 1997).
While these findings suggest that it is critical to ensure training needs are supported with environmental cues and necessary fidelity levels (Milham, Hale, Stanney, Cohn, Darken, & Sullivan, 2004) there is often a tradeoff associated with doing so. As the fidelity of presentation increases, so do the cost, technical expertise required to run and support the system, development and configuration time, and the footprint required to accommodate the system hardware. For this reason, it is important that VE training system implementers integrate system components at the level of fidelity that gives them the most value for the task that they are training. To accomplish this, there is a need for a tool to guide designers on the fidelity level requirements and present trade-offs based on the task that is being trained and the requirements thereof.
|| ||PHASE I: Conduct initial research, develop guidelines, and design a methodology for choosing the optimal fidelity levels for each sensory modality of information presented in VE systems based on cost / benefit analysis (e. g., including training requirements, technology cost, training effectiveness ratio). This tradeoff matrix should be based on comprehensive review of DoD wide training system effectiveness as well as state of the art assessment.
|| ||PHASE II: Develop a prototype interactive computer-based system to drive the design of training systems based on the guidelines established in Phase I. Software architecture should enable users to enter desired parameters and view selection of recommended technology components together with predicted impact on critical performance parameters. Validate the prototype through empirical assessments with targeted user community.
|| ||PHASE III: Produce the final version of the tool and use it to evaluate a current military VR system and guide the design of a VE training system. Market the use of the tool to other sectors that use VE training.
PRIVATE SECTOR COMMERCIAL POTENTIAL/|| ||DUAL-USE APPLICATIONS: This system will have widespread applications to military, government, and private sector organizations in that it will support the development of VE training systems with reduced development lifecycle time/costs. This could be applied to VE training systems used by law enforcement, fire fighting, medical responders, etc.
|| References: ||1. Basdogan, C., Ho, C, Srinivasan, M.A., & Slater, M. (2000). An experimental study on the role of touch in shared virtual environments. ACM Transactions on Computer-Human Interaction, 7(4), 443-460.
2. Blauert, J. (1997). Spatial Hearing: The Psychoacoustics of Human Sound Localization. MIT Press, revised ed., 1997.
3. Feygin, D., Keehner, M., & Tendick, F. (2002). Haptic guidance: experimental evaluation of a haptic training method for a perceptual motor skill. Proceedings of the 10th International Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (Haptics 2002), Orlando, FL, 40-47, March 2002.
4. Hendrix, C. and Barfield, W. (1996). "The sense of presence in auditory virtual environments." Presence: Teleoperators and Virtual Environments 5(3): 290-301.
5. Insko, B., Meehan, M., Whitton, M., & Brooks Jr., F.P. (2001). Passive Haptics Significantly Enhances Virtual Environments. Presence Workshop 2001.
6. Richard, P., Burdea, G., Gomez, D., & Coiffet, P. (1994). A comparison of haptic, visual and auditive force feedback for deformable virtual objects. In Proceedings of ICAT'94 Conference (pp. 49-62). Tokyo, Japan.
7. Storms, R. L. (1998). Auditory-visual cross-modal perception phenomena. Unpublished doctoral dissertation, Naval Post- graduate School, Monterey, California.
8. Swezey, R. W., and Llaneras, R. E. (1997). Models in training and instruction. In G. Salvendy (Ed.), Handbook of Human Factors and Ergonomics (2nd edition, pp. 514-577). New York: Wiley.|
|Keywords: ||VE training system, development lifecycle, system design and development, human system integration (HSI)|