The purpose of this work is to determine the influence of the low beam intensity of motor vehicle headlights on detection conditions in urban traffic. For this purpose, studies with fourteen subjects are conducted on three differently illuminated test roads, in which the low beam intensity is dimmed from off to fully on. At each dimming level, the subjects indicate whether or not they have detected the object, which is realized by a flat target and occurs at sixteen different positions in front of the vehicle. In addition, considerations of the contrast curve and the visibility level are made in order to determine the influence of switched off and fully switched on headlights. The results show that the negative contrast created by the existing street lighting creates detection conditions at least as good as full low beam intensity in almost all cases. The results further indicate that the influence of the low beam intensity increases with decreasing distance to the object and decreasing illumination levels. The results of this work show that an increase in low beam intensity initially leads to poorer detection conditions; thus, the option of reducing low beam intensity should be considered in urban traffic space.

Motor vehicle headlamps are the only light sources that create visibility conditions for the driver in nighttime non-urban traffic. Therefore, a suitable design of these lighting systems is of the highest relevance to allow the driver an early detection of obstacles so that an appropriate reaction is possible. In order to provide a design basis for the headlamps, this article deals with the determination of the minimum required lighting conditions for reliable object detection. For this purpose, studies with drivers were conducted in a light tunnel on a closed test site, and the Visibility Level (VL) required for reliable object detection was considered. Gray cards with a reflectance of 4% were positioned on different positions of measurement grids, and the intensity of the low beam and high beam of a test vehicle was increased step by step until the drivers had detected the gray card. The results demonstrate that a Visibility Level of at least 13.35 is required in non-urban areas in order to reliably detect objects. In addition, the required Visibility Level depends on the eccentricity angle. Thus, the required Visibility Level reaches its maximum value in the foveal area of the field of view and decreases in a Gaussian shape in the periphery.

The purpose of this work is to determine as a function of velocity the minimal roadway luminance that is required to be judged as being bright enough for a driver to perform a nighttime driving task with an adequate feeling of safety. In this context, it shall also be evaluated which areas of the vehicle forefield are most crucial for the driver’s general brightness perception. A field study with 23 subjects and dimmable LED headlights was conducted, in which the subjects were given the task to assess their perceived brightness for different luminance levels caused by the headlights’ low-beam distribution in the vehicle’s forefield on a 5-step rating scale. The experiments were repeated for three different driving velocities of 0 km h⁻¹ (static case), 30 km h⁻¹, and 60 km h⁻¹, respectively. Results for the static case indicate that, for the roadway to be perceived as bright enough by 50% of the subjects, an average roadway luminance of 0.88 cd m⁻² is required in an area up to 32 m in front of the vehicle. Furthermore, a significant effect of driving speed is observed. For example, at 60 km h⁻¹, the luminance must be increased to 1.54 cd m⁻² to be still perceived as sufficiently bright by 50% of the subjects.

In this work, an experiment was designed in which a defined route consisting of country roads, highways, and urban roads was driven by 20 subjects during the day and at night. The test vehicle was equipped with GPS and a camera, and the subject wore head-mounted eye-tracking glasses to record gaze. Gaze distributions for country roads, highways, urban roads, and specific urban roads were then calculated and compared. The day/night comparisons showed that the horizontal fixation distribution of the subjects was wider during the day than at night over the whole test distance. When the distributions were divided into urban roads, country roads, and motorways, the difference was also seen in each road environment. For the vertical distribution, no clear differences between day and night can be seen for country roads or urban roads. In the case of the highway, the vertical dispersion is significantly lower, so the gaze is more focused. On highways and urban roads there is a tendency for the gaze to be lowered. The differentiation between a residential road and a main road in the city made it clear that gaze behavior differs significantly depending on the urban area. For example, the residential road led to a broader gaze behavior, as the sides of the street were scanned much more often in order to detect potential hazards lurking between parked cars at an early stage. This paper highlights the contradictory results of eye-tracking research and shows that it is not advisable to define a holy grail of gaze distribution for all environments. Gaze is highly situational and context-dependent, and generalized gaze distributions should not be used to design lighting functions. The research highlights the importance of an adaptive light distribution that adapts to the traffic situation and the environment, always providing good visibility for the driver and allowing a natural gaze behavior.

Perception-oriented evaluation of automotive headlamps still relies mainly on human-vision photometric criteria, although forward-facing cameras are increasingly safety-critical sensing elements for night driving. This paper benchmarks 16 measured production headlamp light distributions with a simulation chain that combines headlamp spectra and beam patterns, diffuse scene reflection, an imaging-transfer model, and an EMVA-based camera model. The quantitative chain maps scene radiance to sensor-domain signal-to-noise ratio, derives task-specific required signal-to-noise curves from a six-network object-recognition ensemble, and aggregates local threshold satisfaction as region-of-interest coverage across three target reflectances and five driving speeds using WLTP moving-time weights. For the baseline RGB camera, WLTP-weighted coverage ranges from 18.95% to 53.48% across the evaluated light distributions, corresponding to a factor of 2.82 between the weakest and strongest distribution. The camera-parameter sweeps show that favorable beam placement can deliver comparable benchmark coverage with roughly 60% smaller pixel pitch than the weakest distribution, corresponding to an 84% reduction in pixel area, or at materially shorter exposure times. The WLTP-weighted coverage score correlates positively with the established Headlamp Safety Performance Rating, with Pearson $r=0.68$ for the RGB configuration, indicating partial alignment between human-centric and camera-centric illumination needs while confirming that the metrics are not interchangeable. The results identify headlamp light distribution as a primary design parameter for nighttime camera perception and provide a quantitative basis for co-design of automotive lighting and camera-based systems.