A Comparative Analysis of Four Navigation Aids on User Performance in Single User Virtual Environment

Authors

  • Sohail Ghani Department of Computer Science & Information Technology, University of Malakand , Pakistan
  • Shah Khalid Department of Computer Science & Information Technology, University of Malakand , Pakistan https://orcid.org/0000-0002-5670-7510
  • Aftab Alam Department of Computer Science & Information Technology, University of Malakand , Pakistan
  • Muhammad Salam Department of Computer Science & Information Technology, University of Malakand , Pakistan
  • Fakhrud Din Department of Computer Science & Information Technology, University of Malakand , Pakistan https://orcid.org/0000-0001-5025-3223
  • Nasir Rashid Department of Computer Science & Information Technology, University of Malakand , Pakistan https://orcid.org/0000-0002-3231-0711

DOI:

https://doi.org/10.21015/vtse.v13i1.2007

Abstract

In virtual environments (VEs), whether collaborative or single-user, numerous interaction strategies have been developed to facilitate task execution. However, due to the diverse nature of tasks and applications in VEs, these interaction techniques often vary significantly and lack standardization. Consequently, there are no universally accepted or well-organized interaction techniques that can be effectively applied across all VEs. This limitation becomes especially evident in Single User Virtual Environments (SUVEs), where effective communication modalities are essential for task execution. Despite their importance, there has been limited research on systematically comparing communication modalities such as arrows-casting, textual guidance, audio cues, and 3D Map-Liner (3DML) to assess their impact on user performance during task completion in SUVEs.
This study aims to address the above gap by evaluating user performance with different communication modalities in SUVEs. Specifically, it compares the effectiveness of arrows-casting, textual guidance, audio cues, and 3DML for task execution in a VE designed for assembly tasks. A virtual environment was developed where the Dijkstra algorithm was implemented to calculate the shortest distance, ensuring optimized navigation. To conduct the study, 20 undergraduate students were selected to test these navigational aids. The results highlight that arrows-casting demonstrated the highest user performance among the tested modalities, while audio navigation aids showed the lowest performance.
The findings of this study provide valuable insights into the design and selection of communication modalities in SUVEs. The superior performance of arrows-casting suggests that visual navigation aids are particularly effective in guiding users during task execution. On the other hand, the low performance of audio navigation aids indicates the need for further refinement and integration of audio cues in VEs. These results can inform the development of more efficient and user-friendly navigation aids, contributing to improved task completion and overall user experience in VEs. Additionally, the methodology and findings can serve as a foundation for future research on interaction techniques and task optimization in diverse virtual environments.

References

J. M. Albani and D. I. Lee, “Virtual reality-assisted robotic surgery simulation,” J. Endourol., vol. 21, pp. 285–287, 2007.

P. Albus et al., “Signaling in virtual reality influences learning outcome and cognitive load,” Computers & Education, vol. 166, p. 104154, 2021.

M. Blake, “The NASA advanced concepts flight simulator-a unique transport aircraft research environment,” in Flight Simulation Technologies Conference, 1996.

D. Borro et al., “A large haptic device for aircraft engine maintainability,” IEEE Comput. Graph. Appl., vol. 24, pp. 70–74, 2004.

D. Caduff and S. Timpf, “On the assessment of landmark salience for human navigation,” Cogn. Process., vol. 9, pp. 249–267, 2008.

A. Chapanis, “Interactive human communication,” Sci. Am., vol. 232, pp. 36–46, 1975.

C. H. Chen et al., “A desktop virtual reality earth motion system in astronomy education,” J. Educ. Technol. Soc., vol. 10, pp. 289–304, 2007.

J. Chen, “Effective interaction techniques in information-rich virtual environments,” in Proc. Young VR, 2003.

M. Duarte et al., “Learning anatomy by virtual reality and augmented reality: A scope review,” Morphologie, vol. 104, pp. 254–266, 2020.

M. Duckham et al., “Including landmarks in routing instructions,” J. Location Based Serv., vol. 4, pp. 28–52, 2010.

H. A. El-Sabagh, “The impact of a web-based virtual lab on the development of students’ conceptual understanding and science process skills,” 2011.

D. M. Gaba and A. DeAnda, “A comprehensive anesthesia simulation environment: Re-creating the operating room for research and training,” Anesthesiology, vol. 69, pp. 387–394, 1988.

N. Gavish et al., “Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks,” Interact. Learn. Environ., vol. 23, pp. 778–798, 2015.

S. T. Godley et al., “Driving simulator validation for speed research,” Accid. Anal. Prev., vol. 34, pp. 589–600, 2002.

N. Hanna and D. Richards, “Evaluation framework for 3D collaborative virtual environments (the core),” 2014.

S. Harrison and P. Dourish, “Re-place-ing space: The roles of place and space in collaborative systems,” in Proc. 1996 ACM Conf. Comput. Support. Coop. Work, 1996.

M. K. Holden, “Virtual environments for motor rehabilitation,” Cyberpsychol. Behav., vol. 8, pp. 187–211, 2005.

J. N. Howell et al., “The virtual haptic back: A simulation for training in palpatory diagnosis,” BMC Med. Educ., vol. 8, p. 1–8, 2008.

C. Hölscher et al., “Map use and wayfinding strategies in a multi-building ensemble,” in Int. Conf. Spatial Cognition, Springer, 2006.

S. Khalid et al., “Navigation aids in collaborative virtual environments: Comparison of 3DML, audio, textual, arrows-casting,” IEEE Access, vol. 7, pp. 152979–152989, 2019.

S. Khalid et al., “The effect of combined aids on users’ performance in collaborative virtual environments,” Multimedia Tools Appl., vol. 80, pp. 9371–9391, 2021.

S. Khalid et al., “Investigating the effect of network latency on users’ performance in collaborative virtual environments using navigation aids,” Future Gener. Comput. Syst., vol. 145, pp. 68–76, 2023.

N. Khan and A. U. Rahman, “Rethinking the mini-map: A navigational aid to support spatial learning in urban game environments,” Int. J. Hum.–Comput. Interact., vol. 34, pp. 1135–1147, 2018.

A. P. Kiraly et al., “Three-dimensional path planning for virtual bronchoscopy,” IEEE Trans. Med. Imaging, vol. 23, pp. 1365–1379, 2004.

A. Klippel et al., “You-are-here maps: Creating spatial awareness through map-like representations,” Spatial Cognit. Comput., vol. 10, pp. 83–93, 2010.

J. C. Latombe, “Probabilistic roadmaps: A motion planning approach based on active learning,” in Proc. IEEE Int. Conf. Cognit. Informatics, IEEE, 2006.

S. Maidenbaum et al., “The effect of navigational aids on spatial memory in virtual reality,” in Proc. 2020 IEEE Conf. Virtual Reality 3D User Interfaces (VRW), IEEE, 2020.

G. McKenzie and A. Klippel, “The interaction of landmarks and map alignment in you-are-here maps,” Cartogr. J., vol. 53, pp. 43–54, 2016.

T. Monahan et al., “Virtual reality for collaborative e-learning,” Comput. Educ., vol. 50, pp. 1339–1353, 2008.

T. T. H. Nguyen et al., “Guiding techniques for collaborative exploration in multi-scale shared virtual environments,” in Proc. GRAPP Int. Conf. Comput. Graph. Theory Appl., 2013.

W. Quan et al., “Reinforcement learning driven adaptive VR streaming with optical flow-based QoE,” in Proc. 2020 IEEE 18th Int. Conf. Ind. Informatics (INDIN), IEEE, 2020.

M. Raees et al., “Ven-3DVE: Vision-based egocentric navigation for 3D virtual environments,” Int. J. Interact. Des. Manuf. (IJIDeM), vol. 13, pp. 35–45, 2019.

I. U. Rehman et al., “The effect of semantic multimodal aids using guided virtual assembly environment,” in Proc. 2014 Int. Conf. Open Source Syst. Technol., IEEE, 2014.

A. Sampaio et al., “Virtual reality technology applied in civil engineering education,” in Proc. m-ICTE 4, 2006.

H. M. Sayers et al., “Navigational tools for desktop virtual environment interfaces,” Virtual Reality, vol. 7, pp. 131–139, 2004.

K. S. Song and W. Y. Lee, “A virtual reality application for geometry classes,” J. Comput. Assist. Learn., vol. 18, pp. 149–156, 2002.

C. Todd et al., “VirtuNav: A virtual reality indoor navigation simulator,” in Proc. 2014 IEEE Symp. Comput. Intell. Robot. Rehabil. Assist. Technol., IEEE, 2014.

T. Wright and G. Madey, “A survey of collaborative virtual environment technologies,” Tech. Rep., University of Notre Dame, USA, 2008.

E. Yechiam et al., “Easy first steps and their implication to the use of a mouse-based and a script-based strategy,” J. Exp. Psychol. Appl., vol. 10, pp. 89–95, 2004.

N. Yuviler-Gavish et al., “Learning in multimodal training: Visual guidance can be both appealing and disadvantageous in spatial tasks,” Int. J. Hum.-Comput. Stud., vol. 69, pp. 113–122, 2011.

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Published

2025-01-27

How to Cite

Ghani , S., Khalid, S., Alam, A., Muhammad Salam, Din, F., & Rashid, N. (2025). A Comparative Analysis of Four Navigation Aids on User Performance in Single User Virtual Environment. VFAST Transactions on Software Engineering, 13(1), 01–13. https://doi.org/10.21015/vtse.v13i1.2007