Probabilistic approach of pre-estimating life-cycle costs of road tunnels

Abstract

Conceptual pre-estimation of road tunnel costs is a vital yet challenging process during feasibility studies due to the prevailing underground uncertainties and risks. Most existing cost estimation approaches are deterministic, probabilistic methods are limited to a single cost examination. This paper introduces a probabilistic model for pre-estimating road tunnels life-cycle costs. It aims to capture their inherent uncertainty holistically, thus enabling more reliable decision-making at a project’s early stages. The proposed model is developed in three steps: multiple regression analysis, fitting distribution, and Monte-Carlo simulation. The first step unveils the correlations between independent and dependent variables, while the other two steps return the probabilistic descriptions of cost drivers and life-cycle costs. Civil engineering, electromechanical works costs, energy consumption, and operation & maintenance costs are determined as the model’s output variables. A real-world database of 32 dual-bore road tunnels with a total length of 55 km is used to develop probability distributions within reasonable confidence intervals and a sensitivity analysis was performed utilizing tornado charts. The results can assist public authorities and managers in estimating the probability of a specific life-cycle cost and making appropriate decisions in accordance with their risk tolerance.