Enhancing Travel Mode-Choice Modeling with Route-Based Attributes and Explainable Machine Learning
This study proposes an integrated analytical process that combines revealed-preference survey data, route-level attributes derived from a digital trip planner, machine-learning classifiers, and explainable artificial intelligence (XAI) methods to evaluate predictive performance and behavioral interpretation jointly.