Stochastic total cost of ownership forecasting for innovative urban transport systems

This paper presents a financial forecasting method for innovative urban transport systems. The Monte Carlo simulation accounts for future uncertainties such as technology-related and market risks. The method is based on a total cost of ownership (TCO) approach and exemplary results are shown for the introduction of an innovative electric bus system in the city of Berlin. The input parameters are stochastically modeled including future adverse events as well as favorable scenarios for the years 2013, 2020 and 2030. In contrast to determined future scenarios which provide only discrete results, the probability distribution of future system TCO is assessed. The simulation reveals when alternative technologies reach the TCO break-even. The results can be used to derive a technology roadmap. Furthermore, using a suitable visualization the decision-making process for complex investments typical for technology changes (e. g. replacement of a complete bus fleet) is supported.