Technology acceptance model for safety critical autonomous transportation systems

Abstract

It is becoming increasingly clear that a paradigm shift in the way people travel will be seen in the near future. This is due to the ever increasing scope of technology in our lives and a built up public demand for safer, faster, and more efficient transportation options. It is also becoming clear that greater levels of autonomy will enable this paradigm shift to a large degree. However, due to the fact that this will require control over personal safety to be entrusted to the autonomous system, many physiological factors will play an important role in their acceptance. Unfortunately, available technology acceptance models do not include considerations for safety critical systems such as these. This paper proposes a new model which incorporates these considerations focusing on the psychology of control, acceptance, and trust and the factors that influence use of a safety critical technology. This model has been built using data from a series of surveys, simulations, reliability data, and previous technology acceptance models and has been validated using previous research into the usability of autonomous vehicles. The full model and considerations for the improvement of the model as well as further validation techniques is provided. The work in the University of Tulsa Vehicle Autonomy and Intelligence Lab (VAIL) has begun development and verification of the Safety-Critical Technology Acceptance Model and is progressing with the development of the Electronic Car Learning and Intelligence Program Simulator (ECLIPS). Through the investigation of these issues using ECLIPS and user feedback, VAIL is on track to model the acceptance and develop guidelines for the development and implementation of autonomous systems. VAIL is working to research these questions at a fundamental level and describe the topics in a way that can make sure these technologies are in line with the progression of technology and the future of human involvement with these systems.