Personalized Incentive Design for Travel Behavior Modification: Preliminary Results from a Novel Experiment in Hiroshima, Japan

Abstract

We present a novel design framework for generating personalized incentives to promote sustainable travel choices and provide a preliminary report on the empirical results of the framework applied to Hiroshima, Japan. First, this study utilized probe-person survey data collected from the region to learn the value of travel time and the effect of cost parameters for each individual using a mixed logit model. Second, these results were then used to generate personalized incentives following a two part framework. In the first part, five attributes, including total amount of incentive, congestion adjustment, health benefits, environmental benefits, and information provision were varied across different levels and were used as building blocks for the second part, the optimization problem, where the optimal values of incentives which minimize the use of private vehicles were generated. We empirically tested the proposed framework and confirmed an overall decrease in the use of cars. However, only 6 out of the 28 people who participated in the experiment again showed a reduction in the average proportion of private vehicle use.