Most of the existing literature is focused on deriving the short-term influences of shared autonomous vehicles (SAVs) on transportation systems, whereas the long-term potential job accessibility (PJA) effects of SAVs have not yet been fully explored. More specifically, existing research has paid little attention to the impact of urban built environment on the PJA effects of SAVs. To fill in this research gap, this paper focuses on the PJA effects of SAVs under considering urban built environment from the perspective of land use and transportation integration. First, land use and transportation integrated model is used to analyze the PJA effects of SAVs. Then, using multiple regression model, this paper explores the relationship between urban built environment and the PJA effects of SAVs. Finally, using factor analysis and cluster analysis, this paper further distinguishes the change of PJA effects of SAVs based on the built environment attributes. The result of this paper can help decision-makers to understand the PJA effects of SAVs and recognize the negative effects of SAVs.

CICTP