Availability of 3D underground information models is key to designing and managing urban infrastructure construction projects. Buried utilities information is often registered by using different types of location data with different uncertainties. These data variances are, however, not considered in many existing visualization approaches. This study, therefore, aims to enable 3D-representation of uncertainties in underground utility data. To this end, the research team identified four different location parameters (unknown, standard, estimated, surveyed location), and explored how these could be integrated into models that visualize utilities in 3D. As proof of concept, we developed a first 3D uncertainty model for an urban road intersection and implemented this in a handheld augmented reality application. As a next step, we designed an improved 3D visualization model that incorporates standard, estimated, and surveyed location data to estimate utility locations, and to generate cylinder shapes that represent the uncertainty buffer around a visualized utility. The presented approach eventually allows city engineers to better estimate design and construction workspaces. We conclude the paper by elaborating both the contributions and consecutive research steps.
|Title of host publication||Computing in Civil Engineering 2017: Information Modeling and Data Analytics|
|Editors||Ken-Yu Lin, Nora El-Gohary, Pingbo Tang|
|Place of Publication||Seattle, Washington|
|Publisher||American Society of Civil Engineers|
|Number of pages||8|
|Publication status||Published - Jun 2017|