# Research on Transparency Design Based on Shared Situation Awareness in Semi-Automatic Driving
## 6 Discussion  
The main purpose of this paper was to study the effect of interface transparency design according to the SA stage and determine which SA stage had a better transparency design effect.  
We studied the impacts of transparency design of the SA stages on usability, driver workload, and situation awareness in the scenario of dangerous vehicles approaching. According to the three stages of situation awareness and the task model of transparency, we proposed three transparency design schemes. We used the dynamic change of color to show the current environmental information, that is, to increase the driver's SA in the comprehension and projection stages. The results showed that increasing the transparency design of SA significantly improved the interface's usability and improved user satisfaction. Therefore, Design3 outperformed Design2 and Design2 outperformed Design1. Moreover, the transparency design of the SA3 stage (projection) significantly improved the helpfulness of the prompt information on the interface, thus improving the interface's usability.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline  & \multicolumn{2}{c}{**Helpfulness**} \\ \hline \multirow{2}{*}{Projection} & r & 0.488 ** \\  & \(p\) & 0 \\ \hline \(\pi\)\(p\) \textless{} 0.01. & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Results of remarkable otherness analysis.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline  & & **NASA** & **ASQ** & **SAGAT** \\ \hline \multirow{2}{*}{NASA} & r & 1 & & \\  & \(p\) & & & \\ \hline \multirow{2}{*}{ASQ} & r & \(-\)0.364 * & \(1\) & \\  & \(p\) & 0.011 & & \\ \hline \multirow{2}{*}{SAGAT} & r & \(-\)0.020 & \(-\)0.056 & \(1\) \\  & \(p\) & 0.890 & 0.707 & \\ \hline \hline \end{tabular}  
* \(p\) < 0.05.  
\end{table}
Table 3: Results of Pearson correlation analysis.  
Transparency between intelligent systems and humans is a mechanism to promote effective interaction between humans and intelligent systems. Against the background of automated driving in the future, the transparency design of automobile HMI can effectively improve drivers' understanding of environmental information, thus strengthening cooperative driving. The system obtains the environmental information through the sensor, then analyzes and makes predictions, and prompts the driver through the HMI, which can broaden the driver's information perception and foresee potentially dangerous situations.  
Although increasing the SA stage of transparency design can significantly improve the usability, the workload increases accordingly, especially in the attention aspect. Combined with the analysis of the interviews, this may be because the transparency design provides more information and requires the driver's attention to the environment, thus increasing the workload. In more complicated situations, this may be an advantage. For instance, proper attention can prevent drivers from over-trusting the automated driving system and ignoring environmental prompt information, which may lead to dangerous driving.  
There was little difference in the total SAGAT scores among the three design schemes. Design3 had a lower score in the comprehension dimension and a higher score in the projection dimension. Combined with the interview, this may be because Design3 added the prompt information in the stage when the rear vehicle is outside the driver's field of view. The first two designs did not have this prompt. Although this increases the comprehension difficulty for the driver, it lets the driver obtain more danger premonition prompts.