9 papers
BlurDriving: Investigating How Personalized Blur Techniques Impact Drivers' Performance in Virtual Reality
Yuan Li, Mark Colley, Xinyue Gui +4
Distracted driving remains a major safety concern, motivating approaches that aim to reduce visual overload before attention breaks down. However, visual overload varies across ind…
See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers
Ding Xia, Xinyue Gui, Mark Colley +5
Automated vehicles lack natural communication channels with other road users, making external Human-Machine Interfaces (eHMIs) essential for conveying intent and maintaining trust…
Improving Low-Vision Chart Accessibility via On-Cursor Visual Context
Yotam Sechayk, Hennes Rave, Max Rädler +4
Despite widespread use, charts remain largely inaccessible for Low-Vision Individuals (LVI). Reading charts requires viewing data points within a global context, which is difficult…
Peeking Ahead of the Field Study: Exploring VLM Personas as Support Tools for Embodied Studies in HCI
Xinyue Gui, Ding Xia, Mark Colley +9
Field studies are irreplaceable but costly, time-consuming, and error-prone, which need careful preparation. Inspired by rapid-prototyping in manufacturing, we propose a fast, low-…
GTA: Generative Traffic Agents for Simulating Realistic Mobility Behavior
Simon Lämmer, Mark Colley, Patrick Ebel
People's transportation choices reflect complex trade-offs shaped by personal preferences, social norms, and technology acceptance. Predicting such behavior at scale is a critical…
TailCue: Exploring Animal-inspired Robotic Tail for Automated Vehicles Interaction
Yuan Li, Xinyue Gui, Ding Xia +2
Automated vehicles (AVs) are gradually becoming part of our daily lives. However, effective communication between road users and AVs remains a significant challenge. Although vario…