# Operationalizing Dyadic Urban Traffic Interaction Studies: From Theory to Practice
## 4 Results: Aspects of Traffic Interaction Study Design Warranting Trade-Offs  
In setting up experimental interaction studies, experimenters encounter a variety of challenging constraints and considerations that significantly influenced our study design. Here, we share insights into the decision-making processes involved in designing interaction studies. The purpose is not to prescribe a universal method for conducting such studies but rather to illuminate the pragmatic limitations and logistical challenges inherent to this type of research. Although traffic interactions may involve multiple participants, in this paper, for analytical simplicity, we decompose these multi-agent interactions into dyadic components, i.e., we only focus on 2-actor scenarios. This reduction is based on the assumption that at a fundamental level, traffic interactions occur between pairs and are resolved according to the most immediate threats or safety concerns, which allows us to dissect the broader challenges into more manageable segments. As experimenters, we must confront the inherent trade-off between the depth of study in specific scenarios and the generalizability of findings. Not all behaviors or phenomena observed in particular settings will necessarily apply to all scenarios, highlighting the limitations of each study's applicability. This requires us to keep in mind the following decision factors:  
* _Depth vs. Breadth:_ Concentrating on specific scenarios provides depth but may sacrifice breadth and general applicability. * _Quality vs. Quantity:_ Gathering high-quality data in a few scenarios might mean fewer overall observations, affecting statistical power and broader implications. _Cost vs. Coverage:_ Financial constraints may limit the number of scenarios or participants, impacting the study's scope and comprehensiveness. * _Complexity vs. Manageability:_ Studying more complex interactions offers richer insights but can complicate the analysis and interpretation of data, and also create complications with ethical approval from institutional IRBs if the complexity and realism of the setup can potentially create safety concerns for participants. By highlighting these specific decisions and trade-offs necessary in the design and execution of interaction studies, we aim to clarify the requirements for researchers planning to run interaction studies. Besides these broad decision factors, operationalizing interaction studies necessitates a balance of trade-offs in scoping and managing interactions effectively. It is important to determine reasonable ways to break down the comprehensive problem space into manageable, researchable chunks for a focused and effective study. Our brain-storming sessions identified critical decision-making aspects across _four dimensions_ that influence the design of these studies:  
1. **Choice of Scenarios**: Choosing which scenarios to include involves weighing the comprehensiveness against cost and effort. It is impractical to cover every possible scenario, so selecting a subset that offers the most significant insights while being feasible is crucial. 2. **Interaction approach--Vignettes vs. Drives**: Deciding between using short, specific scenarios (vignettes) or longer, continuous driving simulations (drives) affects the depth of data and the naturalism of interactions. 3. **Measures**: Deciding what measurements to take (behavioral, physiological, subjective) and how these metrics can best capture the interactions of interest. The choice of the measures and how they are collected has a direct impact on the determination of whether the interaction approach of the study. 4. **Timing and coordination of Interactions**: Setups that attempt to control the timing to provoke interactions can detract from the natural flow of operating in traffic, presenting a trade-off against naturalism.