Workspace demand changes across space and time, stressing the need to consider space as a limited and renewable resource. Traditional scheduling techniques have not fully handled this issue. This paper proposes a workspace management framework using a game engine to address that. The simulator detects spatial interferences by combining geometric computations and physics simulations. The detected conflicts are filtered through Bayesian inference to detect non-critical scenarios and avoid overestimation. The proposed spatial conflict simulator was tested using a real use case and compared to commercial tools. Results showed that the Navisworks approach detected 58 spatial conflicts (of which only 25% were relevant), the Synchro approach detected 1 spatial conflict, and the proposed approach detected 1 “direct” and 4 “indirect” spatial conflicts. Results show its capability to detect more relevant spatial issues than state-of-the-art tools and avoid overestimations. Construction management teams can adjust or confirm the schedule with that information.

Spatial conflict simulator using game engine technology and Bayesian networks for workspace management

Leonardo Messi
;
Alessandro Carbonari;Berardo Naticchia
2022-01-01

Abstract

Workspace demand changes across space and time, stressing the need to consider space as a limited and renewable resource. Traditional scheduling techniques have not fully handled this issue. This paper proposes a workspace management framework using a game engine to address that. The simulator detects spatial interferences by combining geometric computations and physics simulations. The detected conflicts are filtered through Bayesian inference to detect non-critical scenarios and avoid overestimation. The proposed spatial conflict simulator was tested using a real use case and compared to commercial tools. Results showed that the Navisworks approach detected 58 spatial conflicts (of which only 25% were relevant), the Synchro approach detected 1 spatial conflict, and the proposed approach detected 1 “direct” and 4 “indirect” spatial conflicts. Results show its capability to detect more relevant spatial issues than state-of-the-art tools and avoid overestimations. Construction management teams can adjust or confirm the schedule with that information.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/312707
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