Using an AR-interface for efficient navigation to DRT pick-up locations: a naturalistic field study

Abstract

Shared automated mobility on-demand (SAMOD) is considered as a conven-ient mobility solution in the future. Once the user books a fare via smartphone, the DRT service algorithms set up a pick-up location spontaneously. The user then walks to the flexible meeting point and waits for the shuttle. Here, the users’ main challenge is to navigate and to identify effortlessly the virtual pick-up loca-tion, which has no references in the real world. To achieve high user acceptance of new automated mobility services, providing customers with an intuitive infor-mation system is essential. Especially, when navigating to flexible pick-up loca-tions users must be provided with high user experience. Our developed human-machine interface (HMI) prototype addresses this challenge by using means of augmented reality (AR). It provides users with information in reference to the street environment. This should ensure users’ high rates of pragmatic quality and low rates of cognitive workload when solving the task. A naturalistic real-life exposure study was conducted with 23 young adults. Almost everybody experi-enced smartphone navigation for pedestrians (e.g., Google Maps) before and more than half of the participants experienced AR before. Participants were asked to navigate to a pick-up location in unfamiliar territory. Participants were guided by the AR-HMI prototype through an urban setting and a building. They had to solve the task within a given time frame. Cognitive workload and UX of the prototype were captured. The VRAP prototype provided positive UX espe-cially in terms of high pragmatic quality to the participants. Furthermore, cogni-tive workload was low. Results showed the positive perception of AR-navigation. Implications for application and further research will be discussed.