A Systematic Review of Life-Cycle Cost Analysis in Transportation Infrastructure: Applications to Pavement Preservation, Bridge Rehabilitation, and Long-Term Investment Planning

Abstract

Life-cycle cost analysis (LCCA) has become a foundational economic evaluation tool for transportation agencies seeking to allocate constrained public resources across competing pavement, bridge, and network-level investment needs. This paper presents a systematic review of the LCCA literature as applied to three interrelated domains of transportation infrastructure management: pavement preservation, bridge rehabilitation, and long-term investment planning within transportation asset management (TAM) frameworks. Drawing on peer-reviewed studies, agency guidance documents, and national research syntheses, the review traces the conceptual foundations of LCCA net present value, equivalent uniform annual cost, agency and user cost accounting, and discounting  and examines how these principles have been adapted to the distinct deterioration mechanisms, treatment strategies, and decision contexts of pavements and bridges. The review finds that deterministic, single-point LCCA remains the dominant practice among transportation agencies, even though probabilistic and stochastic approaches (Monte Carlo simulation, Bayesian updating, fuzzy logic) demonstrably improve the treatment of uncertainty in discount rates, traffic growth, material prices, and deterioration timing. At the network and program level, LCCA increasingly underpins transportation asset management plans mandated by federal regulation, shaping multi-year capital programming and preservation-versus-reconstruction trade-offs. Persistent gaps include inconsistent inclusion of user and social costs, limited integration of environmental life-cycle assessment (LCA) with LCCA, weak empirical validation of deterioration and treatment-effectiveness models, and uneven data infrastructure across agencies. The paper concludes by synthesizing common methodological threads across pavement and bridge applications and proposing a research and practice agenda centered on probabilistic modeling, LCA–LCCA integration, climate resilience, and standardized data governance.