Traffic congestion and its urban scale factors: Empirical evidence from American urban areas

This study empirically investigates the causes of urban traffic congestion to bring into focus the variety of beliefs that provide support for policy interventions to mitigate traffic congestion in USt cities. We use a structural equation modeling (SEM) framework and position the analysis at the meso-scale (i.e., neighborhood shapes, sizes, density, land-use mix, street design, distribution of open space) to better align with policy and planning decisions and strategies. The analysis is carried out on 100 metropolitan areas in the USA, with three complementary metrics of urban traffic congestion and 25 factors representing the structural, socioeconomic, and behavioral aspects of urban areas. SEM results demonstrate that congestion is a complicated phenomenon where indirect effects are pathways powerful enough to offset…