Evaluating Multimodal Touchscreen Interfaces for V2V Overtaking Requests in Virtual Reality

Abstract

In future driving, manual drivers will interact with Autonomous Vehicles (AVs) through Vehicle to Vehicle (V2V) communication. This study evaluates the human-machine interaction trade-offs of interface modality stacking for center-stack touchscreens during a cooperative overtaking task. Using a Virtual Reality driving simulator with 26 participants performing a visual secondary distraction task, we compared three configurations: Visual (V), Visual+Haptic (VH), and Visual+Auditory+Haptic (VAH) across normal and time-sensitive requests. Results show that the VAH setup improved overall driver response times, and enhanced request-type classification accuracy for time-sensitive requests. However, an interaction effect revealed that modality stacking sequentially escalated perceived pressure and subjective workload (temporal demand and frustration) specifically during time-sensitive requests. A marginal trend indicated increased system intrusiveness as sensory layers accumulated. These suggest a design trade-off for cooperative driving Human-Machine Interfaces (HMIs): while multi-sensory density dramatically recovers tactical accuracy, it carries an immediate psychological cost that designers must try to mitigate.