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.
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