# Operationalizing Dyadic Urban Traffic Interaction Studies: From Theory to Practice
## 1 Introduction  
The complexities of automated vehicle (AV) interactions with human road users are now recognized as a significant obstacle to their large-scale adoption [1, 2, 3, 4, 5]. Inadequate interaction between AVs and humans could result in accidents if the AVs' actions are not anticipated by human drivers, or traffic congestion and human dissatisfaction if AVs are overly cautious [6]. Hence, there is a pressing need for advancements in understanding traffic interaction, since the substantial societal and economic gains anticipated from the deployment of AVs depend on these vehicles' ability to anticipate and respond appropriately to the behaviors of human driver, pedestrians and other human road users [7, 8, 9]. This urgency highlights existing research questions and introduces new ones regarding how traditional human interactions unfold in traffic--the ability to rigorously examine these interactions, discern nuanced differences, and analyze both the breakdowns and recoveries, is crucial. To drive the research on human behavior in traffic interactions, [PERSON] et al. [10] established a comprehensive, high-level conceptual framework for articulating and examining road traffic interactions from an interdisciplinary perspective. This conceptual framework introduced a precise definition of a \"traffic interaction\" and outlined a taxonomy of behaviors that road users display during such interactions. It offers multiple benefits: besides enhancing communication among researchers through clear definitions, it improves observational methodologies with precise interaction classifications, informs the setting of technical standards for AVs based on a detailed understanding of traffic interactions, and serves as a foundation for developing detailed interaction models. [PERSON] et al. 's work surfaces the need for controlled experiments of road traffic interactions, but the practical operationalization of this framework into human participant studies involves numerous non-explicit challenges and decision points that are not captured in their framework but worth detailing for researchers embarking on the critical challenge of gathering qualitative and quantitative data about traffic interactions. Furthermore, [PERSON] et al. [11] presented a systematic review as a valuable survey of challenging scenarios for automated vehicles (AVs) and vulnerable road users (VRUs), with its focus primarily centering on the identification and classification of critical scenarios from a theoretical and observational standpoint. While these prior works provided a theoretical overview of the diverse possible interaction scenarios, they do not extend to conducting controlled studies with these scenarios. In our work, we build upon prior research, particularly, [PERSON] et al. 's theoretical framework [10] to operationalize experimental studies that enable us to gather qualitative and quantitative data about traffic interaction behavior. We aim to answer a critical question as experimentalists: how should we proceed in operationalizing these interactions for controlled empirical study? A key aspect to focus on is dyadic traffic interactions--interactions that occur between two road users, such as a human-operated vehicle and an autonomous vehicle (see Figure 1). Studying these two-party interactions is essential for understanding the dynamic exchanges and decision-making processes that take place in real-world traffic, where vehicles must constantly respond to the behaviors and actions of others. Operationalizing these dyadic interactions in a controlled setting will allow for more detailed investigation of how autonomous vehicles can safely and efficiently navigate complex situations involving human road users. Our work extends [PERSON] et al. 's work by addressing the practical challenges encountered in setting up study design and conducting real-world or virtual interaction studies.