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A systems-level approach to intersection lighting design has shown that illuminating the intersection box increases drivers’ nighttime visual performance. However, for an intersection lighting design to be effective and accepted, it should not only maximize visual performance but also enhance perceived visibility and minimize glare. The goals of this study were to assess the effects of different intersection lighting designs on these two outcomes. Visibility was assessed with respect to a pedestrian, several targets, and an intersection. Perceptions of visibility and glare were measured using Likert scales, with participants exposed to multiple lighting designs on a realistic intersection. Twenty-four participants completed the study, with an equal number of younger (18–35 years) and older (65+) drivers. The lighting design that illuminated the intersection box had the highest levels of perceived target and intersection visibility and the lowest ratings of glare. For the same lighting configuration, a strong positive correlation was also found between perceived target visibility and previous results on target detection distances. In this configuration, perceived visibility plateaued between 7 and 10 lux of mean intersection illuminance. Increased levels of perceived visibility in different conditions were likely a result of size and contrast differences, and the distribution of the luminaires used. These results suggest that illuminating the intersection box has multiple benefits, in that it not only increases visual performance but also increases perceived visibility and reduces glare.

Nighttime crashes at intersections present a major traffic safety issue in the United States. Existing approaches to intersection lighting design do not account for a driver’s visual performance or the potential interactive effects of vehicle headlamps and roadway lighting. For effective design lighting at intersections, empirical research is required to evaluate the effects of lighting configuration (part of the intersection illuminated) and lighting levels on nighttime driver visual performance. The current study had two goals: First, to quantify visual performance in three lighting configurations (illuminating the intersection box, approach, or both) and second, to determine what lighting levels within each lighting configuration support the best visual performance. The study involved a target detection task completed at night on a realistic roadway intersection. Illuminating the intersection box led to superior visual performance, as indicated by longer target detection distances, fewer missed targets, and more targets identified within a safe stopping distance. For this lighting configuration, visual performance plateaued between 7 and 10 lx of mean intersection illuminance. These results have important implications for the design of intersection lighting at isolated/rural intersections, specifically that illuminating the intersection box is an effective strategy to increase nighttime visual performance for a wider range of driver ages and could also be an energy-efficient solution. Published version

Nighttime crashes at work zones are major concerns for construction workers and motorists. Although in a majority of the U.S. states, department of transportation specifications for work zone lighting mention that contractors should reduce glare for workers and drivers, only two states advocate detailed specifications like light positions, orientation, and light levels. Although some studies have examined the impact of glare from work zone lights on workers and others have calculated veiling luminance levels for drivers in the work zone, the effect of work zone lighting on drivers’ visual performance and glare perception has never been studied in a realistic setting. The goal of this study was to understand the impact of commercially available portable light towers (metal halide, LED, and balloon) and their orientation on drivers’ visual performance and their perceptions of glare. Participants drove through a realistic work zone simulated on the Virginia Smart Road. Visual performance was assessed by a detection task and perception of visibility and glare were assessed by questionnaires. Results indicated that the type of light tower and its orientation affect visual performance and perceptions of visibility and glare. Light towers aimed toward the driver resulted in lowering drivers’ visual performance, both objectively and subjectively. When the light towers were aimed away from or perpendicular to the driver, the visual performance was higher and the differences in visual performance between the types of light towers were minimal. These findings indicate that these orientations should be preferred for work zone light towers.

Driving is often considered a visually oriented task. This visual task is constrained when drivers drive at night. Visibility is reduced because visual cues available during the day are not present at night. This study attempted to develop a link between driver safety and the nighttime visual environment. This research required creating and integrating new technology, observing and collecting data, and developing a model framework called the Dynamic Driver Visual Model (DDVM). Conceptually, a DDVM is a system of rules, statistics, and expectations that can be used to define how a driver collects visual information from the environment. Several information sources were investigated, and several dependent variables were identified. Data were collected on how information from signage, objects, lighting, pavement markings, and other vehicles moderates a driver's visual search of the roadway environment. Several logistic regression analyses were performed on the collected data to identify common characteristics to be implemented in the DDVM. These variables included age, lighting, vehicle headlamps, several different objects, glance time, target luminance, and contrast information. The results suggest that a number of target and visibility elements have nonlinear effects on a driver's detection performance at a variety of detection distances. This paper discusses the implications of these findings and the initial framework of the DDVM. Future research and additional data requirements are also discussed.