Simon Schütte

During the pandemic, UX methods employed in hardware design were restricted or postponed. The typical controlled UX studies were out of reach, as access to users and their exposure to products was restricted. This offered an opportunity in the design of computer mice, found to be in higher demand for working from home. This work describes the development of an adapted method for gathering UX, driven by Kansei Engineering (KE), properly supported by a purposely designed online platform to guide, provide tasks and survey users, KESo. The hypothesis is that remote UX methods allow collecting user feedback with no major loss of subjective data providing similar insights as traditional methods. The emerging idea is that these methods can and will remain useful to support product design. Remote UX can also be autonomous, reducing resources required, thus promising scaling participation, and extending capabilities of gathering emotional responses by adopting new technologies.

This study evaluates four developed external Human–Machine Interface (eHMI) concepts for automated shuttles, focusing on improving communication with other road users, mainly pedestrians and cyclists. Without a human driver to signal intentions, eHMI systems can play a crucial role in conveying the shuttle’s movements and future path, fostering safety and trust. The four eHMI systems’ purple light projections, emotional eyes, auditory alerts, and informative text were tested in a virtual reality (VR) environment. Participant evaluations were collected using an approach inspired by Kansei engineering and Likert scales. Results show that auditory alerts and informative text-eHMI are most appreciated, with participants finding them relatively clear and easy to understand. In contrast, purple light projections were hard to see in daylight, and emotional eyes were often misinterpreted. Principal Component Analysis (PCA) identified three key factors for eHMI success: predictability, endangerment, and practicality. The findings underscore the need for intuitive, simple, and predictable designs, particularly in the absence of a driver. This study highlights how eHMI systems can support the integration of automated shuttles into public transport. It offers insights into design features that improve road safety and user experience, recommending further research on long-term effectiveness in real-world traffic conditions.