Spatiotemporal Heterogeneity Of The Influencing Factors On Urban Residents’ Car Usage

The increasing car usage has resulted many social and environmental problems.Most previous studies examined the general correlations between the determinants and the usage pattern of private car by establishing global regression models.These models ignore the variation of travel behavior across temporal and spatial dimensions,and analysis methods targeting one scale and dimension possibly lead to wrong bias and overlooks certain momentous details.Considering this research gap,this paper explores the influence of determinants on the time-of-day car usage pattern,using the multi-source data collected from the city of Kunming,China.It applies a geographically and temporally weighted regression(GTWR)model and multi-scale geographically weighted regression(MGWR)to investigate the heterogeneous relationship between on the mode share of private car and the factors of individual attributes and built environment.The empirical results are as follows:(1)Based on Household travel survey data,a detailed analysis of individual and household attributes of the sample in the study area as well as residents’ travel mode share and house-work distance under different socio-economic attributes was conducted.The POI dataset,road network data,residential neighborhood data,bus stop and busline data were used to construct a basic database of built environment in Kunming.After establishing the scale of the research units in this paper,the spatial characteristics of urban built environment and the spatio-temporal characteristics of car use are further visualized and analyzed.(2)The spatio-temporal heterogeneity of residents’ socio-demographic attributes and built environment on the hourly mode share of private car was analyzed by using the GTWR model with the 800*800m grid as the basic research unit.The results show that the GTWR model produces better goodness-of-fit compared with ordinary least squares regression(OLS),as well as GWR model.It confirmed that both of selected the socio-demographic and built environment attributes have heterogeneous effect on the car share in time and space dimensions.A visualization method is applied to analyze the temporal variation of the coefficients of socio-demographic attributes and built environment variables,and to reveal the spatial distribution of the effects of determinants during peak hours.(3)Using the divided 800*800m grid as the basic research unit and combined with the temporal perspective(morning and evening peak,off-peak),the MGWR model is used to analyze the heterogeneous scales of the influence of residents’ socio-demographic attributes and built environment on the mode share of private car.The results show that the MGWR model has a higher goodness-of-fit.Based on the results of the MGWR model,the heterogeneity of the scales of the effects of variables on the mode share of private cars in different time periods is analyzed,and the visualization method is applied to analyze the spatial variation of the coefficients of the variables.(4)Based on the results of spatiotemporal heterogeneity study of the impact of built environment and socio-demographic on residential car use,insightful policy recommendations for different urban areas are presented to encourage the reduction of car usage and alleviate urban traffic problems.