A survey to measure cognitive biases in mobility choices and responses to urban policy

Recent urban policies are trying to encourage soft mobility, yet observations show an inertia or a slow evolution: people tend to still stick to the individual car despite policies inciting them to switch to other modes. We suggest that this can be explained by cognitive biases influencing the perceptions of the different mobility modes. In this paper, we describe a survey about the perceptions of 4 mobility modes (car, bus, bicycle, walking) and the preferences of users for 6 modal choice factors. This survey has gathered 650 answers in 2023, that are published as open data. In this study, we analyse these answers to highlight the influence of 3 cognitive biases on mobility decisions: halo bias, choice-supportive bias, and reactance. Our results support the hypothesis that cognitive biases are a plausible explanation to the (lack of) response to urban policies. Our biased decision model and collected data can serve several purposes. It can be used to initialise a virtual population with realistic attributes, and simulate their mobility decisions in reaction to various urban policies. The decision model can also be implemented in interactive simulators to illustrate the impact of cognitive biases on decisions. Work is also ongoing to design a simulation-based serious game where the player takes the role of an urban manager faced with planning choices to make their city more sustainable. • Describe a model of mobility choice based on 6 decision factors. • Present the methodology of a survey to measure users’ preferences for these factors, as well as their perceptions of how 4 mobility modes (car, bus, walk, bicycle) fill these criteria. • Discuss the results of this survey, that gathered 650 answers, and are published as open data. • Analyse these results to highlight the influence of 3 cognitive biases in mobility decisions: halo, choice-supportive bias, and reactance. • Show how this model and data can be used as a basis for a simulator aimed at predicting modification of the modal distribution in a town in reaction to urban policies.