Space-time dynamics of cab drivers' stay behaviors and their relationships with built environment characteristics

Understanding cab drivers' stay activities is essential for planning and managing certain urban facilities. This study analyzes cab drivers' stay behaviors using a taxi GPS trajectory dataset collected in Wuhan, China. By extracting cab drivers' stay activities from the dataset, we measure the activity frequency at the level of traffic analysis zones (TAZs) and examine their spatiotemporal dynamics. We then derive several built environment indicators and assess their associations with these activities using ordinary least squares regression (OLS) and geographically weighted regression (GWR) models. According to the results, the stay frequency decays dramatically over the TAZs, indicating that these activities tend to be concentrated in particular areas of the city. The rates of decay, as reflected by the rank-size and power-law distributions, are similar on weekdays and weekends. Cab drivers' stay activities exhibit similar spatial patterns during the same period on weekdays and weekends. The adjusted R-squared of OLS is 0.742 for weekdays and 0.676 for weekends, which suggests a close relationship between stay activities and built environment characteristics. The GWR models further reveal the spatial variations of the activity-environment linkage across the study area. The study provides useful insights that support future urban design and transport planning.