Measuring Users' Willingness to Use Shared Autonomous Vehicles Based on an Extension Technology Acceptance Model

The development of shared autonomous vehicles (SAVs) is an important direction in intelligent and green transportation, but the relevant research is insufficient. The choice behavior of SAV passengers needs additional analysis. To address this, we first constructed an extended technology acceptance model (ETAM) by introducing three latent variables: perceived risk, service quality, and social influence. A hybrid choice model was then constructed by integrating the latent variables of the ETAM, individual socioeconomic attributes, and travel mode attributes into a multinomial logit model. The probability of passengers choosing an SAV is taken as an evaluation index to measure passengers' willingness to take an SAV. Finally, based on the Stated Preference survey data, the model parameters were calibrated, and the pathways of latent variables and key influencing factors were obtained. The impact of key factors on passengers' willingness to take an SAV was studied through elastic analysis. The elastic analysis revealed that perceived usefulness (0.0502) is the most significant factor, followed by travel cost (0.0401), perceived ease of use (0.0385), and waiting time (0.0350). This study can provide theoretical support for relevant enterprises and government departments to develop and promote SAVs.