Representing travel cost variation in large-scale models of long-distance passenger transport

In this paper we show that travel cost variation for long-distance travel is often substantial, even within a given mode, and we discuss why it is likely to increase further in the future. Thus, the current praxis in large-scale models to set one single travel cost for a combination of origin, destination, mode, and purpose, has potential for improvement. To tackle this issue, we develop ways of accounting for cost variation in model estimation and forecasting. For public transport, two methods are developed, where the first method focuses on improving the average fare, whereas the second method incorporates a submodel for choice of fare alternative within a demand model structure. Only the second method is consistent with random utility theory. For car, cost variation is related to long run decisions such as car type choice and employment location. Handling car cost variation therefore implies considering car type choice and workplace choice rather than different options related to a specific trip. These long-term choices can be considered using a car fleet model.