To synthesize evidence on how Building Information Modeling (BIM) and digital twins enhance economic efficiency and safety in U.S. highway infrastructure through intelligent asset management. Guided by PRISMA 2020, searches across engineering, transportation, and standards repositories (2000–August 2023) yielded 3,146 records. After removing 1,012 duplicates, 2,134 titles/abstracts were screened; 378 full texts were assessed; 92 studies were included (empirical, mixed-methods, and rigorously reported gray literature). Data were extracted on model uses, governance, and outcomes; heterogeneity precluded meta-analysis, so a structured narrative synthesis was undertaken. Evidence clustered across four domains. (1) Economic efficiency: sixty-three studies reported fewer design clashes, reduced rework and RFIs, and more stable schedules and quantities under 3D/4D/5D coordination. (2) Predictive maintenance and lifecycle value: forty-nine studies linked digital-twin condition monitoring and deterioration forecasting to earlier, better-targeted treatments and fewer emergency interventions. (3) Safety and risk reduction: fifty-two studies associated time-aware staging, traffic management visualizations, and real-time hazard indices with lower exposure in work zones and shorter detection-to-response intervals. (4) Intelligent asset management: fifty-eight studies documented benefits when digital as-builts, IFC/COBie handovers, and sensor feeds populated governed asset registers, improving auditability and budget formulation. Cross-jurisdictional comparisons (forty-one studies) showed stronger, more consistent outcomes where open standards and owner information requirements were embedded in procurement and delivery. Across ninety-two studies, BIM provides the authoritative, object-based backbone for asset information, while digital twins synchronize that information with operational state. Under interoperable standards and clear governance, this pairing consistently supports cost control, safety performance, and reliable maintenance planning in U.S. highway programs.
Islam et al. (Wed,) studied this question.