How Autonomous Vehicles Shape Urban Traffic Sustainability: An Empirical Study Based on Structural Equation Modeling

Currently, urban traffic flow is an increasing problem, and achieving sustainability in urban mobility is essential for enhancing both mobility and the quality of life. This study investigates the factors influencing urban traffic sustainability from two critical perspectives: autonomous vehicle policy governance and citizen perception. By utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM), this study analyzes data from 502 valid responses gathered through online surveys. The findings reveal that, from the citizen perception perspective, both accessibility and safety play a significant role in advancing urban traffic sustainability, while smart mobility modes were found to have no substantial impact. From a policy governance standpoint, land transportation planning did not significantly influence citizens’ perceptions of accessibility, safety, or smart mobility. In contrast, vehicle management measures were positively correlated with these dimensions. Furthermore, the scope of service point support was found to enhance accessibility and smart mobility but did not have a noteworthy effect on safety. Vehicle deployment allocation, however, was positively associated with improvements in accessibility, safety, and smart mobility. This study offers valuable insights for urban traffic policy formulation, emphasizing the pivotal role of regulatory frameworks, vehicle management strategies, and urban infrastructure in fostering sustainable urban mobility.