Traffic and Transport Ergonomics on Long Term Multi-Agent Social Interactions: A Road User’s Tale

Abstract

AbstractThere are public debates concerning the meaning highly automated vehicles (HAVs) will possess in society and on road social interactions, with the topic of autonomy being frequently stressed. The de-contextualised and abstract discussion has influenced the development of the on-road Multi-Agent Social Interaction (MASI) concept. By addressing socially sensitive road users’ co-experiences with HAVs, a range of social situations, and how the social dimensions comes to play in different future scenarios may aid scholars and manufacturers gain insights as well as challenge perceived assumptions. For prolific future mobility research and development, we need to consider long-term automation effects to on-road social interactive behaviours – an under-addressed and often overlooked issue. Thus, we revised ideas that infer social interaction patterns, in hopes to try to interrogate and situate these patterns within the context of MASI. These viewpoints are compared and integrated to formulate a structured and explorative framework, describing MASI in the context of space sharing, as this is important to consider in the early stage of HAV development. This paper aims to situate the experiences of road users within an illustrative urban context, as real-world commuting experiences may include multiple people interacting with HAVs at the same time. Further offers significant contributions, which is a description of “MASI”: in short, as on-road social interaction consisting of different road users (humans and automated vehicles), as agents that socially interact with and react to each other, simultaneously. In essence, a classification of co-experiences that users’ may exhibit in in-group social interactions with HAV and interaction dynamics with automation tailored for different road-user types, and further supports several multimodalities. This framework is helpful in envisioning better-equipped systems, models, theories, human factors requirements for interaction designed strategies, and in-group-out-group humans-automation collaborative research.KeywordsAutomated vehiclesHuman factorsTraffic and transport ergonomicsMASILong-term automation effectsUser experiences