Heiko Hecht
The best way to measure cybersickness
The Fast Motion Sickness Scale (FMS) has become a valuable tool to assess motion sickness whenever quick unobtrusive measures need to be taken. It is well-anchored and provides scalable, quantitative data, however, it is indifferent to individual symptoms. If anything, it focuses on nausea and neglects many other symptoms of motion sickness such as eye-strain or dizziness. We seek to exploit the advantages of traditional symptom-based questionnaires without subscribing to their disadvantages. To do so, we propose to diversify the FMS to include the most important symptom groups. In particular, we propose the use of three separate FMS variants, each focusing separately on nausea, oculomotor discomfort, and dizziness. We report first findings with these variants of the FMS.
Christoph Freiherr von Castell
Visual acceleration signals for pedestrians’ time-to-collision estimation
Pedestrians estimating the time-to-collision (TTC) of approaching vehicles mainly rely on distance and speed, often neglecting acceleration. This can lead to TTC overestimation and unsafe crossing decisions when vehicles accelerate. Previous work showed that a light band around a vehicle’s windshield indicating acceleration can reduce this bias, but it remains unclear whether such signals help pedestrians distinguish between different acceleration rates. In a VR traffic scenario using the prediction-motion paradigm, thirty participants judged TTC for vehicles moving at constant speed, low (1.5 m/s²), or high acceleration (3.0 m/s²) under three conditions: no signal, a binary signal (light band on/off), and an informative signal conveying acceleration magnitude (flashing frequency). Both signals reduced TTC overestimation, but only the informative signal led to differentiated TTC estimates for low versus high acceleration. We discuss these findings in the context of traffic safety and the design of intuitive vehicle-to-pedestrian communication.
Bio: Christoph von Castell received a PhD in Psychology from Johannes Gutenberg University Mainz, Germany, where he holds a lifetime position as a senior lecturer. His academic work focuses broadly on human perception, with research interests that include space and interior perception, time-to-collision estimation, depth and color perception, visual illusions, and the perception of upright. His research program includes virtual and augmented reality to examine how environments shape perceptual judgments. Additional lines of research address the influence of ambient color on cognition and how expectation shapes time perception. He teaches experimental methods, data analysis, and research design.
About the Colloquium
The Mind Meets Machine series is a new monthly forum at Aalto CS that brings together researchers and students across disciplines. We focus on the intersection of mind and technology, from cognitive mechanisms to applied AI, aiming to share cutting-edge research, spark dialogue, and foster collaborations across schools and departments.