Exploring the value of digital twins for information management in highway asset maintenance
Mengtian Yin, Varun Kumar Reja, Ran Wei, Ioannis Brilakis, Brian Sheil, Federico Perrotta, Alix Marie d’Avigneau, Linjun Lu
Abstract
Highway agencies face challenges managing dispersed asset data across maintenance processes and information systems, hindering efficient retrieval of dynamic road information for timely interventions. A Digital Twin (DT)-based Information Management Framework (IMF) offers a promising solution based on a Foundation Data Model, Reference Data Libraries, and Integration Architecture. However, it is currently unclear how DT models of highway infrastructure systems based on a connected data ecosystem can be used in maintenance and how they benefit stakeholders. This paper describes results from a survey exploring DTs' potential in highway maintenance, starting with interviews with 20 experts to understand current processes, followed by a questionnaire survey to identify phases, features, applications, and use cases perceived as important by practitioners for road DTs. 183 responses reveal that DTs are widely deemed useful for asset deterioration prediction, strategy-making for routine maintenance planning, and scenario design for road investigation and repair in project-level maintenance. • Explored Digital Twin Information Management Framework for highway maintenance. • Interviewed 20 highway experts to understand current processes and inefficiencies. • A global survey to identify key applications and use cases of road digital twins. • Key features of road digital twins include prediction, simulation, and diagnostics. • Experts highlight DT benefits in improved lifecycle management and lower costs.