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Citation
Articles | Volume V-4-2022
https://doi.org/10.5194/isprs-annals-V-4-2022-319-2022
https://doi.org/10.5194/isprs-annals-V-4-2022-319-2022
18 May 2022
 | 18 May 2022

STATE DEPARTMENTS OF TRANSPORTATION’S VISION TOWARD DIGITAL TWINS: INVESTIGATION OF ROADSIDE ASSET DATA MANAGEMENT CURRENT PRACTICES AND FUTURE REQUIREMENTS

A. Ammar, H. Nassereddine, and G. Dadi

Keywords: Digital Twins, Departments of Transportation, Transportation Asset Management, Roadside Assets, Data Management, Data Collection

Abstract. Transportation Asset Management (TAM) is a data-driven decision-making process to maintain and extend the serviceability of transportation assets throughout their lifecycle. TAM is an extensive data process that requires accurate and high-quality information for better decision-making. A significant challenge faced by state Departments of Transportation (DOTs) is the need to allocate their limited funds to optimize their assets’ performance. The criticality of this challenge increases when state DOTs need to manage a wide variety of assets distributed along with a vast network. To address this challenge, a new paradigm of digitizing the management of the built environment is emerging and is perceived to highly depend on the integration of several technologies namely on Digital Twins. Digital Twins, by definition, are the connection between the physical and the digital aspects of an asset, thus, aligning with the overarching objective of asset management of leveraging the use of the asset information (i.e., digital aspect of the asset) to improve the asset’s performance throughout its lifecycle (i.e., physical aspect of the asset). At the core of implementing Digital Twins is having the right data collected for use throughout the lifecycle of the asset. Thus, realizing the potentials of Digital Twins in supporting state DOTs to manage their transportation assets and the anticipated benefits, this paper investigated the current practices of state DOTs in digitizing the Data Collection for Roadside Asset Systems by developing and distributing a web-based survey. Five major Data Collection variables and seven Roadside Asset Systems were considered. Furthermore, this paper presents a case study from a leading DOT in digitizing the management of the built environment to further understand the requirements of implementing Digital Twins to support transportation asset data management.