## 4 Discussion  
When looking only at the third part of this three part paper series, it might seem that only using 15 test subjects for the gaze analysis seems like a small number of test subjects, especially considering that a total of 54 test subjects participated in the study presented here. However, using 15 test subjects with an average of over 2.5 h each and a sample rate of 120 Hz for the eye tracking system led to a total of more than 900 million gaze vectors that had to be analysed for the nighttime driving alone. Nonetheless, it is the analytical approach embodied in this and earlier papers that is the main novel outcome of the present work, more so than the resulting headlight distribution. For this reason, the decision to only evaluate the data test subjects with calibration results below 2.0\({}^{\circ}\), would be expected to influence the acquired results positively rather than negatively. However, one major point needs to be addressed. All of the data shown in this part, as well as in part two, were acquired on the same single route through Germany. So, while the data, when compared to similar data found by other studies, seems similar and by that representative of overall road conditions, it cannot truly be representative for the world, for Europe, or even for Germany. Therefore, the proposed light distribution is to be taken with the required scepticism. A more appropriate approach would be to consider this paper as a starting point and as a novel way to create an optimized headlight distribution. On the same note, it should be noted, that the light distribution shown in Figure 9 has been created by simply using all the available data for urban roads, rural roads, and motorways and weighting them all equally. Obviously different cars are created with different driving types in mind. Small cars that are mainly designed to be driven inside of large cities, for example, could use a different light distribution than cars that are typically designed for longer journeys, and which will be mainly driven on motorways. Figure 9: Mirrored and smoothed proposed new headlight distribution based on real traffic and gaze data as well as on detection tests under ideal road conditions  
Additionally, with the current technology and increasing possibilities of those technologies in modern headlights, a scenario is possible where thousands of different light distributions could be programmed into a single headlamp. Then, the next step would be to go through datasets such as the ones created for the present studies, and to define more granular situations in which different light distributions might increase traffic safety. Following this, the light distributions for those different situations could be optimized. The three-part approach taken in this and the accompanying papers (parts one and two) illustrate how it might be possible to use empirical visual detection data from closed-road investigations and apply the resulting photometric requirements to real-world roadway environments such as the ones underlying the test drives in this and the previous papers. Of course, the data and real-world environments are limited in the current study. As a result, this paper should be considered as a starting point for future research rather than a definitive optimized headlight distribution. Conceptualization, J.K.; data curation, J.K.; formal analysis, J.K.; methodology, J.K.; software, J.K.; supervision, T.Q.K. ; validation, J.K.; visualization, J.K. and A.E. ; writing--original draft, J.K. and A.E. ; writing--review and editing, J.K., A.E., J.D.B. and T.Q.K. ; project administration, J.K. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. All data generated or analysed to support the findings of the present study are included in this article. The raw data can be obtained from the authors, upon reasonable request.