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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations

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Publication Number:  FHWA-HRT-15-047     Date:  August 2015
Publication Number: FHWA-HRT-15-047
Date: August 2015


Evaluation of The Impact of Spectral Power Distribution on Driver Performance

CHAPTER 9. Summary

This project is a comprehensive review of the applicability of mesopic functions to roadway applications. While the model to determine the impact of mesopic adaptation to visual performance has been well-established and verified, both in the laboratory and in some very carefully prescribed experiments, the real-world applicability of the model has remained in question. Determining the impact of mesopic lighting on high-speed roadways was the focus of this effort. In addition, an MPI system for highlighting pedestrians was developed and tested. The MPI system’s effect on visibility may have also been affected by the overhead-lighting source’s SPD and level; pedestrians on the roadside might be detected in the periphery, where mesopic effects occur.

This project was developed as a stepwise approach to these problems. The first two steps were to develop a scoping experiment that defined the nature of the effect of the spectral distribution of overhead lighting on visibility and to provide guidance for the development of the subsequent experiments. The primary outcomes from this scoping experiment were that both the type and level of overhead lighting significantly affected the detection and recognition of objects on the roadway. This was also evident for objects that were off of the roadway. One of the primary determinants for detection was the color of pedestrian clothing and targets in the roadway, thus indicating that color contrast is a significant component of object detection. The results also indicated that roadway lighting uniformity has an important role in object detection. The final aspect was that of headlamp color and intensity. In scenarios when overhead lighting was used, headlamp configuration did not affect visibility.

These results drove the direction of the next two experiments. The first was an investigation of conditions when headlamps have an impact on object detection and when they do not have an impact. The second was an investigation of the applicability of the mesopic model to roadway lighting.

Before these experiments were performed, however, an investigation of the applicability of an MPI system was conducted. Although the scoping experiment showed a minimal spectral effect of the headlamp color on detection distance, two headlamp colors were used to further explore this relationship. A mock-up MPI system was created with servo-activated headlamps that either tracked the pedestrians as the vehicle approached or highlighted them for a short time as the vehicle approached. The results of this experiment were that use of the MPI system resulted in both shorter detection distances and an increase in detection rate. Headlamp color did not seem to have a significant impact on detection. When the MPI system highlighted an area across from a pedestrian, participants’ detection rates and distances for that pedestrian were lower. This highlights the importance of careful design in a full-featured MPI system; participants’ behavior indicated that they expected it to work properly, so it must not produce false positives, which could distract drivers from actual roadside hazards.

The next experiment was an investigation of the interaction of vehicle headlamps and overhead lighting on roadway-object detection. Small targets and a pedestrian were located in specific locations along the roadway that created high- and low-visibility conditions. The overhead lighting was then dimmed and headlamps turned off and on while participant drivers tried to detect the objects. Results indicated that the impact of the headlamps varied by object size. For most lighting levels, the overhead lighting was the dominant force driving object detection, but that was not the case when the overhead lighting was at the lowest levels. The results of the experiment show that when a vehicle approaches a negatively contrasted target and the vehicle’s headlamps begin to illuminate that target, the target contrast passes from negative to positive contrast and, importantly, through a point of invisibility—zero contrast—during that transition. Therefore, it is desirable for roadside objects to be positively contrasted at all times. The results also show that headlamps affect pedestrian luminance up to 91.4 m (300 ft) away. Headlamps were the driving factor for orientation-recognition distances, the direction the object was facing. The applicability of these results are critical for roadway lighting design. Headlamps dominate object recognition and also drive adaptation luminance. Therefore, the effect of the SPD of the roadway lighting may be overridden by the headlamps’ effect on adaptation level and the contribution of headlamp illumination to object luminance.

The other experiment resulting from the scoping experiment considered the mesopic model. Here both static and dynamic target detection experiments allowed the research team to evaluate the mesopic model in the field. The static portion of the experiment was performed by determining the threshold contrast for small targets, and the dynamic portion examined target detection from a moving vehicle. In both cases the drivers were instructed to fix their gaze on the roadway, with the targets located at a number of peripheral angles. Gray targets were used to minimize the contribution of color contrast on object detection. The results indicate that overhead-lighting level significantly affected object detection; higher adaptation levels resulted in a lower threshold contrast. The results also showed that in the dynamic experiment, higher speeds typically resulted in longer detection distances. In terms of the mesopic model, for white overhead-lighting sources, the experimental results corresponded well to the model; however, for HPS lighting, they did not. An issue with the mesopic model could be that it does not include a term for eccentricity that accounts for different retinal sensitivities at different angles. The main conclusion was that although the mesopic model predicted some of the results at lower lighting levels, it also has limitations.

The final experiment performed did not attempt to limit driver eye glances or fix eccentricities at detection. This experiment included an MPI system, overhead lighting, two speeds, and pedestrian detection at different offsets from the roadway. The results indicate that for pedestrians close to the roadway, there was no impact of overhead lighting’s spectral distribution on detection distance. For those pedestrians, adaptation luminance was the most influential factor on visibility. For pedestrians farther from the roadway, spectral effects were more significant, but those results might not be applicable to roadway lighting design, because objects that far away would have to be moving fairly quickly and on a collision path with the vehicle to become a hazard. The MPI performance results were similar to those of the initial MPI experiment. The MPI reduced detection distances and increased detection rates for objects in the periphery. The results of this experiment show that in a natural driving environment at the speeds tested, there is limited applicability of the mesopic model to lighting design. It is likely that drivers scan the roadway and detect objects in the fovea, where mesopic effects are not seen. Headlamps might also cause a high adaptation luminance, further limiting the applicability of the mesopic model to lighting design for nighttime driving.



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