Multimodality on the Road: Towards Evidence-Based Cognitive Modelling of Everyday Roadside Human Interactions

Abstract

We propose an evidence based methodology for the systematic analysis and cognitive characterisation of multimodal interactions in naturalistic roadside situations such as driving, crossing a street etc. Founded on basic human modalities of embodied interaction, the proposed methodology utilises three key characteristics crucial to roadside situations, namely: explicit and implicit mode of interaction, formal and informal means of signalling, and levels of context-specific (visual) attention. Driven by the fine-grained interpretation and modelling of human behaviour in naturalistic settings, we present an application of the proposed model with examples from a work-in-progress dataset consisting of baseline multimodal interaction scenarios and variations built therefrom with a particular emphasis on joint attention and diversity of modalities employed. Our research aims to open up an interdisciplinary frontier for the human-centred design and evaluation of artificial cognitive technologies (e.g., autonomous vehicles, robotics) where embodied (multimodal) human interaction and normative compliance are of central significance.