## 5 Conclusions and Outlook  
The presented article deals with the determination of necessary Visibility Levels VL in nighttime non-urban road traffic in order to reliably detect objects. For this purpose, detection studies are carried out in a light tunnel and on a closed test site. Gray cards with a reflectance of about 4% are used as detection objects, which are positioned in a measurement grid in front of the vehicle to determine object detection as a function of the distance and eccentricity angle. For this purpose, object distances from 40 m to 100 m are considered. Therefore, both the low beam and high beam intensities are varied in the detection studies, while the drivers are tasked with signaling the object detection. The results of the light tunnel study demonstrate that a Visibility Level of 13.35 is required for a detection probability of 90%. This value is comparable to the field factor of 12.7 determined by [PERSON] [18]. If the more realistic situation on the closed test site is considered, the required Visibility Level increases to 25. Furthermore, the angle dependence of the required Visibility Level can be observed in the light tunnel. This follows a Gaussian course and shows the maximum required Visibility Level in the foveal area (0\({}^{\circ}\)). This course confirms the results of the investigations of [PERSON] [18] and [PERSON] [34]. In order to further increase the validity of the conducted studies in the future, the following extension options should be considered. The gray cards with a reflectance of about 4% used in the conducted studies represent a worst-case consideration. For future studies, it is therefore advisable to vary the object size, object shape, and reflectance and thus investigate their influence on the detection conditions. Unfortunately, due to the pandemic situation, the number of drivers participating in the study is rather small. Therefore, the driver collective should be expanded, especially with drivers of a higher age, in order to specifically investigate the influence of observer age on the object detection probability. Furthermore, the results of the present study demonstrate that the eccentricity angle between the object and the driver has a significant influence on the required Visibility Level for a reliable object detection. Thus, the driver's gaze behavior should also be taken into account in future studies. The results of the presented article can be used to optimize future vehicle headlamp light distributions to ensure the reliable object detection in nighttime non-urban traffic. Segmented light distributions, whose luminous intensities are designed on the basis of the required Visibility Level, could thus be implemented. This would have the advantage that, on the one hand, the object detection is ensured by sufficient luminous intensity and, on the other hand, the glare for other road users can be minimized by switching off the respective segments, as required. This type of adaptive lighting control is already being implemented under the name of a glare-free high beam and represents the state of the art [50,51]. Within the context of the study carried out, static tests are performed because they guarantee the reproducibility of the study and, consequently, the results obtained compared to dynamic tests, which are very suitable for the validation of light distributions. Due to the greater realism of dynamic studies, they should be performed as a next step to validate the light distributions generated by the static tests. Such studies can also be used to determine the influence of the driving task on the object detection probability. Conceptualization, A.E., D.H. and N.K. ; Data curation, A.E., N.K. and T.V. ; Formal analysis, A.E. and N.K. ; Methodology, A.E., D.H. and N.K. ; Software, A.E., D.H., N.K. and T.V. ; Supervision, T.Q.K. ; Validation, A.E. ; Visualization, A.E. ; Writing--original draft, A.E. ; Writing--review and editing, A.E., D.H., N.K., T.V., K.K., M.A.P. and T.Q.K. ; Project administration, A.E. ; Funding acquisition, A.E., D.H. and T.Q.K.