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

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

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关键字: Taxi GPS trajectories;Stay behaviors;Spatiotemporal analysis;Built environment;Geographically weighted regression

作者单位: Institute of Cartography and Geoinformation, ETH Zurich, Zurich, Switzerland;Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong;The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China;Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong;Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong;Department of Human Geography and Spatial Planning, Utrecht University, 3584 CB Utrecht, The Netherlands;Institute of Cartography and Geoinformation, ETH Zurich, Zurich, Switzerland;Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong;The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China;Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong;Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong;Department of Human Geography and Spatial Planning, Utrecht University, 3584 CB Utrecht, The Netherlands

摘要: 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.