Determining causality in travel mode choice

• Published in: Travel, behaviour & society behaviour & society, 2024-07, Vol.36, p.100789, Article 100789
• Main Authors: Chauhan, Rishabh Singh, Riis, Christoffer, Adhikari, Shishir, Derrible, Sybil, Zheleva, Elena, Choudhury, Charisma F., Pereira, Francisco Câmara
• Format: Article
• Language: English
• Subjects: Activity based models; Causality; Travel behavior; Travel mode choice models
• ISSN: 2214-367X
• DOI: 10.1016/j.tbs.2024.100789

•A novel methodology is proposed to understand causality in travel mode choice.•Causal discovery algorithms are combined with Structural Equation Modeling.•Four causal discovery algorithms are tested on survey data.•This study is a major advancement to the existing correlation-based modeling. This article presents one of the pioneering studies on causal modeling in travel mode choice decision-making using causal discovery algorithms. These models are a major advancement from conventional correlation-based techniques. We propose a novel methodology that combines causal discovery with structural equation modeling (SEM). This modeling approach overcomes some of the limitations of SEM by combining the strengths of both causal discovery and SEM. Causal discovery algorithms determine causal graphs from observational data and domain knowledge, and SEMs estimate direct causal effects and test the performance of causal discovery algorithms. In this study, we test four causal discovery algorithms: Peter-Clark (PC), Fast Causal Inference (FCI), Fast Greedy Equivalence Search (FGES), and Direct Linear Non-Gaussian Acyclic Models (DirectLiNGAM). The results show that DirectLiNGAM based SEM model best captures causality in mode choice behavior. It passes several goodness-of-fit tests, including Root Mean Square Error of Approximation (RMSEA) and Goodness-of-Fit Index (GFI), and it achieves the lowest Bayesian Information Criterion (BIC) value. The analyses are conducted on data collected from the 2017 National Household Travel Survey in the New York Metropolitan area.