TASK DECOMPOSITION AND LEVEL OF COMPLEXITY TO SELECT THE CONTENT OF UNDERGROUND UTILITY NETWORK MODEL

Abstract

Accurate and efficient 3D spatio-semantic Underground Utility Network (UUN) models looks indispensable for the whole cycle of its planning, construction, maintenance, and all kinds of the decision-making process. We do believe that UUN model should be able to provide multiple representations, considering data accessibility and model comprehensibility, but how to define these levels of detail (LoD)? In this research, we made the hypothesis that LoD selection is related to the complexity of task to be performed. This paper aims at designing a decomposition method of the decision-making task and defining the level of complexity to evaluate the task. Then based on the complexity level, select the content of UUN model that is most suitable for the task with the best representation. This paper discusses the possible connections between the LoD of 3D UUN model and with decision-making tasks, providing solutions to guide decisions of model selection.