Methods for Quantitative Risk Analysis for Travel Demand Model Forecasts

Travel demand forecasting models have played a critical role in transportation planning; these models support the evaluation of policies, programs, and projects that involve complex interactions between the activity system and the transportation system. Both the state of the art and the state of the practice in travel demand modeling have advanced considerably during the many decades since the original four-step model structure was conceived. However, the models are not now, and never will be, perfect representations of the systems they represent; so there are inevitably uncertainties about the forecasts that these models generate. Travel demand forecasts are important in many applications, for example, in determining whether a given alternative is financially or technically feasible or meets some benefit threshold. In these applications, uncertainties in model forecasts may translate directly into risks of not accomplishing the objectives related to the decision to implement or not implement the alternative. For projects that involve outside financing, this threshold varies greatly between equity and lender participants because of the differing risk–reward profiles. Several previous papers described the uncertainties associated with travel demand forecasting and recommended ways of improving the state of the practice. Among those recommendations is the application of formal quantitative risk analysis methods. This paper summarizes the existing literature and describes the application of one relatively straightforward but robust approach for conducting quantitative risk analysis with travel demand forecasting models. The formal risk analysis approach described here can assist by providing a more complete evaluation of a project's likelihood of achieving specified objectives. The approach can support the development of traffic and revenue forecasts beyond a most likely scenario to consider any level of risk assumed by a project sponsor, debt provider, or rating agency.