Integrating Virtual Reality and Building Information Modeling for Improving Highway Tunnel Emergency Response Training
Auteur(s): |
Xinhua Yu
Pengfei Yu Chao Wang Di Wang Weixiang Shi Wenchi Shou Jun Wang Xiangyu Wang |
---|---|
Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 20 septembre 2022, n. 10, v. 12 |
Page(s): | 1523 |
DOI: | 10.3390/buildings12101523 |
Abstrait: |
During the last two decades, managers have been applying Building Information Modeling (BIM) to improve the quality of management as well as operation. The effectiveness of applications within a BIM environment is restrained by the limited immersive experience in virtual environments. Defined as the immersive visualization of virtual scenes, Virtual Reality (VR) is an emerging technology that can be actively explored to expand BIM to more usage. This paper highlights the need for a structured methodology for the integration of BIM/VR and gives a generic review of BIM and VR in training platforms for management in infrastructures. The rationales for fire evacuation training were formed based on the review. Then, methods of configuring BIM + VR prototypes were formulated for emergency response in highway tunnels. Furthermore, a conceptual framework integrating BIM with VR was proposed to enable the visualization of the physical context in real-time during the training. The result indicated that, extended to the training system of highway management via the “hand” of BIM, the VR solution can benefit more areas, such as the cost of fire evacuation drills in highway tunnels and the tendency of accidents to occur in the emergency response. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
9.23 MB
- Informations
sur cette fiche - Reference-ID
10700215 - Publié(e) le:
11.12.2022 - Modifié(e) le:
15.02.2023