Accommodating Perceptual Conditioning in the Valuation of Expected Travel Time Savings for Cars and Public Transport

Abstract

Travel time variability (i.e., random variations in travel time) leads to a travel time distribution for a repeated trip from a fixed origin to destination (e.g., from home to work). To represent travel time variability, a series of possible travel times per alternative (departure time, route or mode) are often used in stated choice experiments. In the traditional models, the probabilities associated with different travel scenarios (e.g., arriving early, on time and late) shown in the experiments are directly used as weights. However, evidence from psychology suggests that the shown probabilities may be transformed (underweighted or overweighted) by respondents. To account for this transformation of probabilities, this study incorporates perceptual conditioning through a non-linear probability weighting function into a utility maximisation framework, within which the empirical estimate of the value of expected travel time savings is estimated. The key advantage of this framework is that the estimated willingness to pay value can be directly linked to the source of utility (i.e., the probability distribution of travel time), while taking into account the perceptual transformation of probabilities.