State departments of transportation (DOTs) increasingly use visualization and modeling technologies for delivering transportation projects across the United States. Advanced and innovative technologies have the ability to improve various construction processes and tasks while making the construction process more efficient and productive. Visualization and modeling technologies, which include building information modeling for infrastructure, light detection and ranging, virtual reality, and augmented reality, are becoming more commonplace in transportation construction. Yet, the use of these technologies varies among state DOTs. The intent of this study is to investigate the use of visualization and modeling technologies for transportation construction. This study employed a triangulation research methodology including an extensive literature review, survey questionnaire of DOTs, and seven case studies. Results of the study show that 92% of state DOTs use visualization and modeling technologies for construction. Then, 81% of DOTs use visualization and modeling technologies for constructability reviews, 38% use them for documentation of as-builts and simulating bridge and structure construction, and 35% use them for quality management, inspections, and monitoring progress of work. The main barriers to using visualization and modeling technologies include legal concerns with using digital models as contract documents, incompatibilities in software and hardware between the DOTs and contracted parties, and the appropriate knowledge, skills, and abilities required to use visualization and modeling technologies for construction. The findings from this study provides valuable information for state DOTs to approach their implementation and use of visualization and modeling technologies for transportation construction delivery.
CITATION STYLE
Harper, C. M., Tran, D., & Jaselskis, E. (2021). Implementation of Visualization and Modeling Technologies for Transportation Construction. Journal of Civil Engineering and Construction, 11(1), 29–40. https://doi.org/10.32732/jcec.2022.11.1.29
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