OpenBIM-based Integrated Urban Road Maintenance Planning Framework

Description

Hong Kong's road network is the most heavily used in the world, and proper maintenance of its roads is crucial to provide safe and efficient services for users. Thus, project planners for road pavement maintenance projects in urban areas are required to find optimal maintenance plans (i.e., dimensions and schedules of work zones, resource applied) that minimize all user travel and construction costs (i.e., total costs), which are interconnected with each other, in a timely manner. To this end, integrated processes that analyze construction costs, durations, and travel times and search for optimal plans are necessary. However, existing construction process simulation methods, which are required for the realistic estimation of construction durations, cannot comprehensively consider impacts of workspace conflicts. In addition, existing methods that adopt microscopic traffic simulations to consider interrupted traffic flow in the urban road network cannot accommodate temporary road network in a timely manner. Existing optimization methods for road maintenance projects are limited in their ability to consider comprehensive decision variables. Existing data schema (e.g., Industry Foundation Classes [IFC]) cannot comprehensively provide the representations required for the analysis and optimization processes in an integrated manner. As current fragmented decision-making processes prevent planners from rapidly carrying out such analyses for various alternatives, planners encounter difficulties when developing optimal road maintenance plans. To overcome these limitations, this research proposes an openBIM-based integrated urban road maintenance planning framework. This framework consists of one data schema and one optimization methodology for urban road maintenance projects. First, the team will extend the existing representations in IFC and openGIS standards to formally represent comprehensive information (e.g., workspaces, temporary road network) required for BIM-based construction process simulation and microscopic traffic flow simulation for the maintenance projects via interviews and case studies. The data schema will enable planners to explicitly describe the information required for maintenance projects in a comprehensive and integrated manner. Second, for the optimization methodology, the research team will extend the existing BIM-based construction process simulation methods to consider workspace conflicts and the existing microscopic traffic flow simulation method to consider secured boundaries for the temporary road network. In addition, the team will tailor the existing Bayesian optimization methods to the urban road pavement maintenance plans. The methodology will enable planners to rapidly generate an optimal maintenance plan. Consequently, this research will contribute the framework to the field of construction management for road maintenance projects.