Research was conducted to determine the nighttime visibility of flat pavement-marking tape, patterned pavement-marking tape, and wetweather pavement-marking tape in dry, wet (just after rainfall), and simulated rain conditions (ongoing 1-in./h rainfall). The measures of effectiveness were the detection distances, the eye-fixation distributions, and the pavement-marking retroreflectance. The research was sponsored by FHWA. The experiment was conducted on a test track in Cottage Grove, Minnesota. This test track had a section at which 1-in./h rainfall could be simulated. Eleven women and seven men, ranging in age from 55 to 74 (average age 62.5), participated in this study. The participants drove the experiment vehicles along the pavement-marking treatments. The participants were to state the earliest point at which they could see the end of the pavement markings. The retroreflectance of each pavement-marking material was measured with three handheld retroreflectometers under the three weather conditions according to ASTM E-1710 (dry), ASTM E-2177 (wet recovery), and ASTM E-2176 (continuous wetting). The retroreflectance values were correlated to the detection distances to determine the ability of each ASTM test method to predict visibility performance under the corresponding weather condition. The wet-weather tape performed best for detection distance, followed by the patterned tape and the flat tape. The detection distances were longest in the dry condition, shorter in the wet condition, and shortest in the simulated rain condition.

The severity of wildfires is increasing and has driven increases in nighttime fire activity. Enhanced capability to detect the active burning regions of wildfires at night could significantly improve the effectiveness of wildfire management operations. Potassium line emission in the NIR near 770 nm is a signature of active burning. We test the use of multi-band imaging from an aircraft at night to distinguish a wood-burning fire from artificial light sources. We find that a simple ratio of the signals in two broad bands, one including 770 nm, effectively discriminates the fire from artificial light sources. This offers the possibility of nighttime fire detection with high spatial resolution using silicon sensors sensitive in the NIR.

The purpose of this field study was to compare nighttime traffic sign legibility under static (parked) and dynamic (driving) conditions using bottom-up legibility as a measure of performance. Drivers need more traffic sign luminance to recognize words on signs while driving than they need when sitting still (parked). The primary reason for this increase in luminance demand is that the driver must periodically shift visual attention away from the sign to attend to the driving task. Legibility performance was assessed with N = 18 observers driving at an assigned speed of 48 km/h (30 mph). Participants ranged in age from 55 to 77 with a mean of 66 years. At a distance of 36 m (120 ft) there was a 117% increase from the static to the dynamic demand luminance. At a longer distance of 55 m (180 ft), there was a 256% increase, and at a distance of 57 m (187 ft), the increase was 556%, and beyond that distance, we could no longer generate a luminance that was sufficient to meet the dynamic demand.

Development of TarVIP 1.0, a computer model for predicting the detection distances of normal and UV activated pavement markings was recently completed at the Operator Performance Laboratory (OPL). Two Sherwin-Williams UV activated pavement marking samples, four UV headlamp units (Ultralux, Visteon, Cibio and Labino brands), and the UV filter covering the Labino UV headlamp unit were characterized in terms of their fluorescence coefficients, spectral emissions, and spectral transmissivity, respectively. The TarVIP model properly accounts for a complete three-dimensional representation of the roadway-headlamp-driver geometry. Veiling luminance due to fog is modeled using the Mie Scattering theory. The model consists of physical and human performance subsystems. Besides the aforementioned physical subsystem items, the human performance subsystem uses an extensive human visibility contrast threshold database to represent the human capabilities and limitations of pavement marking detection. The model was used to obtain the visibility distances under various levels of fog density, UV activated pavement marking and UV headlamp efficiencies. The resulting visibility distances show some potential benefits and some inadequacies of the UV headlamps and UV activated pavement markings.