Virtual reality (VR) can be a very effective tool to evaluate built environment to support improvement of pedestrian and other vulnerable road user safety. However, in order to draw actionable conclusions from VR it is important to understand the degree to which pedestrians’ perceptions and behaviors match across real and virtual environments. In this study, participants experienced equivalent real and virtual environments and performed similar tasks in each. Tasks included pedestrian’ intention to cross, estimation of speed and distance of an approaching vehicle, and the perceived safety and risk of crossing a road. Pedestrians’ presence was also measured in all environments. Result showed that there were no differences between the real and virtual environments for most of the tasks. Significant differences between real and virtual environments were observed in the estimation of speed and measures of presence. These results have important implications for using VR as tool to evaluate pedestrian safety in built environments.

In the last decade, pedestrian fatalities at night, especially at midblock locations, have been increasing at an alarming rate. Lighting is an effective countermeasure in reducing nighttime crashes. However, few studies have evaluated the effects of crosswalk lighting on pedestrian visibility at midblock locations. There is an existing need to develop lighting designs that increase pedestrian visibility. Further, the safety effects of lighting have never been directly compared to other pedestrian-crossing treatments (such as flashing signs, rectangular rapid flashing beacons (RRFBs), etc.). Thus, in order to make effective recommendations for increasing nighttime pedestrian visibility, it is important to compare the visibility benefits of crosswalk lighting designs with and without pedestrian-crossing treatments. This study evaluated the visual performance of five midblock crosswalk lighting designs along with two pedestrian safety countermeasures at three light levels on a realistic midblock crosswalk. Visual performance was measured by calculating the distance at which the participants could detect a child-sized mannequin under the evaluated conditions. The results showed that midblock crosswalks should be illuminated to an average vertical illuminance of 10 lux to ensure optimal pedestrian visibility. Lighting designs that render the pedestrian in positive contrast (area in front of the crosswalk is illuminated) are recommended to increase pedestrian visibility. It is also recommended that pedestrian-crossing treatments, such as RRFBs and flashing signs, should be used with lighting to increase nighttime visibility.

Almost all existing research about intersection lighting indicates that the presence of lighting reduces nighttime crashes. This study aimed to quantify the effect of lighting level and lighting quality on the night-to-day (ND) crash ratios at rural intersections. Illuminance measurements were collected from 99 lighted and unlighted rural intersections in Virginia. The measurements were then combined with the crash data, obtained from the Virginia Department of Transportation, for each of the intersections. A negative binomial regression was used to model the crash and lighting data. Results indicated that lighting level (average horizontal illuminance) significantly affected the ND crash ratios at rural intersections. A 1 lux (lx) increase in the average horizontal illuminance at all rural intersections in Virginia corresponded to a 7% decrease in the ND crash ratio. For the lighted intersections, a 1 lx increase in average horizontal illuminance corresponded to a 9% decrease in the ND crash ratio. The largest decrease in the ND crash ratio was for unlighted intersections, where a 1 lx increase in the average horizontal illuminance corresponded to a 21% decrease. Stop-controlled intersections had smaller ND crash ratios than signalized intersections. Intersections with a posted speed limit of less than or equal to 40 mph had lower ND crash ratios than intersections with a posted speed limit of greater than 40 mph. Each of the results is discussed with respect to the impacts of the lighting measurements on nighttime driving safety and overall visibility.

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.

With the advent of light-emitting diode technology being applied to roadway lighting, the spectral power distribution of the light source is becoming much more important. In this experiment, the detection of pedestrians at five adaptation levels under three light sources, high pressure sodium and light emitting diodes of two colour temperatures was measured in realistic roadway scenarios. The results show that while the light source type was not significant, an increase in adaptation luminance increased the detection distance. As the offset of the object to the roadway increased, some spectral effects became more significant; however, this effect was not consistent across all angles of eccentricity. The conclusions from this work indicate that mesopic factors may not be applicable on high-speed roads.

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.