Exploring the effect of built environment on spatiotemporal evolution of traffic congestion using a novel GTWR model: a case study of Hefei, China.

Understanding the impact of the built environment on traffic congestion can provide reliable references for alleviating traffic congestion. Previous research has explored traffic congestion evolution but often overlooks two key aspects: the frequency of congestion state updates and the spatial-temporal impact of built environment features. Based on data from Hefei, China, we propose a novel geographically and temporally weighted regression (GTWR) model that integrates temporal variables and spatial grids into the traditional GWR model. The empirical results show that public facilities most significantly impact congestion during morning peak hours, scenic spots during afternoon peaks, and motorcycle services in the evening. The study also reveals the rules for the spatiotemporal impact of the built environment on traffic congestion. Finally, the comparison of models shows that the GTWR model outperforms the OLS and GWR models. The findings can guide traffic managers in creating targeted strategies to enhance transportation system efficiency. [ABSTRACT FROM AUTHOR]