A Rank Dependent Scheduling Model

This paper proposes an analytical framework for scheduling decisions of road travelers that takes into account probability weighting using rank dependent utility theory. The fundamental difference with the standard scheduling model based on expected utility is that the probabilities of arrivals are treated in a non-linear way. This paper shows how scheduling decisions are affected by the weighted probabilities of the traveler. We derive the costs of non-optimal chosen departure times because of probability weighting and show that if the parameterized probability weighting function is similar to what has been found for gambling, the costs of probability weighting for morning peak car travelers are around 3 per cent. For the full range of parameters tested, we find costs in the range of 0-24 percent of total travel costs