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This Interim Technical Bulletin recommends procedures for conducting Life-Cycle Cost Analysis (LCCA) of pavements, provides detailed procedures to determine work zone user costs, and introduces a probabilistic approach to account for the uncertainty associated with LCCA inputs. The Bulletin begins with a discussion of the broad fundamental principles involved in an LCCA. It discusses input parameters and presents simple examples of traditional LCCA in a pavement design setting. It discusses the variability and inherent uncertainty associated with input parameters, and provides recommendation on acceptable ranges for the value of time as well as discount rates. It explores the use of sensitivity analysis in traditional LCCA approaches. User costs are a combination of delay, vehicle operating costs, and crash costs. Each of these cost components is explored and procedures are presented to determine their value. Given the power and sophistication of today’s computers and software, simulation techniques such as Monte Carlo are recommended for incorporating variability associated with LCCA inputs into final results.
This Interim Technical Bulletin recommends procedures for conducting Life-Cycle Cost Analysis (LCCA) of pavements, provides detailed procedures to determine work zone user costs, and introduces a probabilistic approach to account for the uncertainty associated with LCCA inputs. The Bulletin begins with a discussion of the broad fundamental principles involved in an LCCA. It discusses input parameters and presents simple examples of traditional LCCA in a pavement design setting. It discusses the variability and inherent uncertainty associated with input parameters, and provides recommendation on acceptable ranges for the value of time as well as discount rates. It explores the use of sensitivity analysis in traditional LCCA approaches. User costs are a combination of delay, vehicle operating costs, and crash costs. Each of these cost components is explored and procedures are presented to determine their value. Given the power and sophistication of today’s computers and software, simulation techniques such as Monte Carlo are recommended for incorporating variability associated with LCCA inputs into final results.