There is a close interaction between the urban built environment and the spatial behavior characteristics of individuals in time. Youth groups are an important group in urban development, and their travel affects the overall efficiency of the city. This study uses cell phone signaling data and POI data to build linear regression models and geographically weighted regression models, respectively, to analyze the impact of built-up environment on the peak hour travel of youth groups. It is found that there are similarities in the morning and evening peak models, and there are significant differences in travel in time and space; the residential population and job density have significant effects on the travel of the youth population, and commuting travel is still the most important travel, and there is separation of jobs and residences; the construction of new cities in Shanghai is steadily advancing, and the accessibility and equity of urban services and facilities need to be strengthened.

youth group, built environment, linear regression model, geographically weighted regression model