Risk Analysis to Account for Uncertainty in Benefit–Cost Evaluations of Intelligent Transportation Systems

Abstract

Benefit–cost analyses of intelligent transportation systems (ITS) have produced point estimates of the benefit–cost ratios of ITS deployments. The need to perform risk analyses to account for the uncertainty in ITS benefit and cost parameters is discussed. It is recommended that the analyses be based on overall assessments of the combination of point estimates, confidence limits, and probability distributions of the benefits, costs, and benefit–cost ratios. Two methods are presented for performing risk analyses with Monte Carlo simulation. The first allows the calculation of the parameters required for the risk analysis procedure in the ITS Deployment Analysis System (IDAS) sketch planning tool. No methodology has been proposed for this calculation in the literature. The second method is a generalized risk analysis procedure that can be implemented in sketch planning tools. The procedure was implemented in this study as part of the screening analysis for ITS. The results indicate that for the investigated case studies, procedures that base the risk analyses on varying the output variables (as is the case in IDAS) will result in benefit–cost ratios with medians (50th percentiles) that are close to those obtained with procedures that are based on varying the input variables. However, the confidence limits produced may be different. The results also indicate that risk analyses produce wide confidence intervals of the estimated benefit–cost ratios, reflecting the high levels of uncertainty in the values of ITS benefit and cost parameters reported in national benefit–cost studies and databases.