Cross-National Analysis of Drivers’ Route Diversion Behavior: Insights from a 13-Country Study

Abstract Understanding driver diversion behavior under disrupted network conditions is critical for both short- and long-term traffic management and planning. This paper aims to investigate the factors influencing drivers’ route diversion behavior under disrupted network conditions by analyzing survey data collected from 13 countries. The dataset of 9,652 responses contained categorical, numerical, and Likert scale data via questions about commute characteristics, traffic information acquisition habits, attitudes toward route diversion under a wide range of considerations, and sociodemographic information. Initial logistic regression analyses grouped countries by diversion likelihood. Then, exploratory factor analysis and structural equations modeling were used to identify latent factors influencing diversion behavior and confirm the directionality and magnitude of the relationships between these factors and other variables from the dataset, such as the previously formed country groups. Findings show that travel times and delays increase the likelihood of diversion both directly and indirectly through increasing the likelihood of traffic information search, which further increases diversion likelihood. Residing or working in urban areas and not in suburban areas also increased the likelihood of diversion, as did residence in Egypt or India when compared with all other countries surveyed. The avenues for research available to such a dataset are many, including building on previous international studies of mobility behavior, uncertainty, risk avoidance, and employee behavior, as well as comparisons of data collection methods and differences in geography, climate, culture, government type, urban form, and more.