Proceedings of the Annual Meeting of the Cognitive Science Society

The purpose of this paper is to determine whether a par-ticular context factor among the variables that a researcheris interested in causally affects the route-choice behavior ofdrivers. To our knowledge, there is limited literature that con-sider the effects of various factors on route choice based oncausal inference.Yet, collecting data sets that are sensitive tothe aforementioned factors are challenging and the existingapproaches usually take into account only the general factorsmotivating drivers route choice behavior. To fill these gaps,we carried out a study using Immersive Virtual Environment(IVE) tools to elicit drivers route choice behavioral data, cov-ering drivers’ network familiarity, education level, financial-concern, etc, apart from conventional measurement variables.Having context-aware, high-fidelity properties, IVE data af-fords the opportunity to incorporate the impacts of human-related factors into the route choice causal analysis and ad-vance a more customizable research tool for investigatingcausal factors on path selection in network routing. This causalanalysis provides quantitative evidence to support drivers di-version decision. The study also provides academic sugges-tion and reference for investing in public infrastructure anddeveloping efficient strategies and policies to mitigate trafficcongestion.