This research plan outlines a sequential, three-stream approach to designing and evaluating a transparency cue for automated vehicles. The plan treats the overall problem as one of human factors and design , using a systematic, evidence-based process to arrive at an optimal solution. The research is framed within a design thinking methodology, which involves distinct stages of development, from initial user consultation to final in-situ testing. This method ensures that the final design solution is selected through a methodical process, and the entire project can be contained within a single ethics application 

Stream 1: 

This initial study serves as the Discover and Define phases. It explores the problem space by engaging directly with drivers to establish a robust set of designs for an easily interpretable transparency cue. 

Methodology: 

Semi-structured cognitive interviews will be conducted. The methodology will allow for open-ended, exploratory questioning to elicit genuine user insights without being overly prescriptive. Participants will be asked to imagine a scenario and describe how a system could best communicate information for quick and accurate understanding. Follow-up questions will explore their ideas in more detail (e.g., "Where should it be on the dash?", "What should it look like?").  

The participant sample will be representative, including a cross-section of users with varying levels of experience (e.g., novice and experienced drivers, EV and non-EV drivers) to ensure a broad range of perspectives are considered. Recruitment will continue until a point of saturation is reached, where no new themes are emerging from the interviews. A sample size of up to 30 participants is anticipated.  

Outcome: The qualitative data will be thematically analysed to develop a set five design candidates for testing in the next stage.  

 

Stream 2: Empirical Evaluation of Prototypes 

Objective: As the Develop phase of the Double Diamond, this study will take the design candidates from Stream 1 and explore their effectiveness. The goal is to empirically test these multiple potential solutions to identify the most robust and effective design.  

Methodology: 

A controlled experiment will be conducted, potentially online using a platform like Mechanical Turk or Qualtrics to access a broad sample.  

Participants will be exposed to the design candidates within a relevant visual context, such as a short video or image.  

The evaluation will be multi-faceted, testing several key dimensions of usability. This includes:  

Attention: Does the cue effectively and quickly attract the user's attention?  

Interpretability: Can users understand the meaning of the cue accurately, quickly, and without prior instruction?  

Cognitive Load: Is the cue easy to understand, or is it distracting or cognitively loading for the user?  

The study will also examine the robustness of the designs by testing how interpretation is affected by individual differences or other factors.  

Outcome: Data from this experiment will provide an evidence base to select the single, optimal transparency cue to carry forward into the final validation study.  

Stream 3: High-Fidelity Validation 

Objective: This final stream serves as the Deliver phase of the Double Diamond. The purpose is to validate the effectiveness of the single, optimized design selected in Stream 2 by testing it in a realistic and dynamic context. 

Methodology: 

The optimized transparency cue will be implemented in a high-fidelity driving simulator for in-situ testing. 

The driving task will involve a mix of manual and automated driving periods. During the drive, participants will be presented with various hazards to assess their response. It will be made clear to participants during the informed consent process that simulated crashes may occur as a potential outcome of the driving scenarios. 

This study will serve as a summative evaluation to measure the practical impact of the cue on driver behavior and task performance to determine if it works "in practice". 

Key Variables & Measures: 

Independent Variable: The presence of the optimized transparency cue. 

Dependent Measures: The primary outcome will be the effect on driver attention and adaptive responses, including: 

Driving Behaviours: Measures of how drivers respond to events and hazards on the simulated roadway will be collected to determine if the cue leads to more adaptive performance. 

Attentional Allocation: The study will seek to understand if the cue improves the driver's attention towards critical information and events in the driving environment. 

Moderating Variables: The impact of select individual differences may still be examined in the final analysis if warranted by findings from the previous streams. 

Outcome: This summative evaluation will provide the concluding evidence on the real-world effectiveness of the systematically designed transparency cue 

 

 ***Focus on the opening paragraph - make it more readable its not long and the links between the model and the streams could be clearer.