To See or Not To See – The Effect of Object Recognition on Users’ Trust for "Automated Vehicles"

Paper in proceeding, 2016

While automated vehicle technology progresses, potentially leading to a safer, more efficient traffic environment, many challenges remain within the area of human factors, such as user trust for Automated Driving (AD) vehicle systems. Previous research has focused on creating a guiding framework for implementing trust-related factors into the Human-Machine-Interaction (HMI) interface in automated vehicles. This paper presents the result of a first validation test of the trust framework. To test the factor “feedback” in the form of Object Recognition, three OR-concepts with different levels of system transparency were tested in a level 3 (NHTSA) Wizard of Oz vehicle. Results indicate that presenting feedback through OR can increase the level of trust for the system, and that users prefer moderation – neither too much nor too little feedback. The paper also demonstrates the framework’s usefulness in guiding HMI designers in the trust-based development process with the help of a well-defined design-space.