The invention belongs to the research technology field of urban transportation planning and traffic big data, and provides a method to quantitatively analyze the impact of urban built environment on road travel time. Firstly, the average speed and the built environment attribute information of each small road section are extracted, based on the taxi GPS data and the spatial geographic information data on the research route. Then, taking the average speed of each small section as the dependent variable, the built environment attribute of the road section is used as the key independent variable, and the virtual variable of the nearest intersection type of the road section is used as the adjustment variable. The regression analysis is carried out with considering the interaction between the key independent variable and the adjustment variable, and the key independent variables which significantly affect the average speed of the road sections are selected from the obtained regression results. Finally, the extracted key independent variables are brought into the geographic weighted regression model for quantitative analysis. The effect and benefit of the invention is to provide decision-making basis for transportation planning and management departments to adjust urban built environment attributes and improve road network operation efficiency.
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