Research On The Receptive Intention Of Self-Driving Vehicles From A Human-Computer Interaction Perspective

Today,with the rapid development of artificial intelligence,autonomous vehicles with the application of AI technology are becoming familiar to the public step by step.As service products with national focus,self-driving vehicles have a strong momentum of development.As the highest level of autonomous vehicles,the self-driving car is still in the test,and people’s attitude towards it is not clear.There are great differences between this new technology and traditional cars in many aspects,and it is facing a new market environment.Therefore,the study of its public recognition and acceptance is an important guarantee for it to enter the market.In order to make up for the shortcomings of previous studies,this research develops and verifies a comprehensive model from the perspective of human-computer interaction,combining the stimulus-organism-response theory and the Technology Acceptance model,and describes the psychological driving factors and internal mechanism behind its acceptance process from a psychological point of view.The model assumes that perceived usefulness(PU),perceived ease of use(PE)and perceived interaction(PI)are the main stimulus variables that affect individual cognition.After receiving these stimulus,people weigh the perceived risk(PR)and perceived benefit(PB),and finally get receptive intention(I).And the model takes into account the moderating role of artificial intelligence preference(AIP).An online survey of potential consumers in China was conducted in the form of questionnaires,and the collected data were processed and analyzed by using Amos 23.0 and SPSS 22.0 software combined with statistical methods.The results of empirical analysis show that PU,PE and PI all positively influence PB and negatively influence PR;PB positively influences I,while PR negatively influences I;artificial intelligence preference enhances the positive effect of perceived benefit on receptive intention and weakens the negative effect of perceived risk on receptive intention.The results of the research put forward some suggestions on the design and operation of self-driving vehicles.