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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



Effect of Overhead-Lighting SPD on Driver Visual Performance

The primary result of this project shows that the SPD of overhead lighting affects object visibility but only in selected conditions. Adaptation luminance affected detection distance more so than light source type and correlated color temperature. Eccentricity affected the extent to which overhead-lighting spectrum affected detection distance; objects closer to the line of sight of the driver were less affected by source spectrum than objects farther from the line of sight. This may be a result of driver scanning behavior. For off-axis pedestrians, broad-spectrum overhead lighting had greater, albeit not statistically significant, color-recognition distances than HPS lighting. It is noteworthy that this result is related to the light sources used for the experiment, and this result may vary based on a different light source.

The contrast of the overhead lighting system appeared to affect pedestrian visibility. At the time of detection, pedestrians contrasted more against the background under HPS lighting than they did under the other light sources, likely because HPS lighting is less uniform and created bright lines across the roadway. This result may be related to the light source intensity distribution and the inefficiencies in lighting design with the HPS light source. Future experiments should investigate the effect of overhead lighting uniformity on object detection.

Combined Effect of Overhead Lighting and Headlamps on Driver Visual Performance

When only overhead lighting was used and headlamps were off, objects could be detected from farther away than with overhead lighting and headlamps on because adding vehicle headlamps increased the ambient luminance of the forward roadway, increasing adaptation luminance and decreasing contrast sensitivity. The result was that with headlamps, distant objects were more difficult to detect under the same overhead lighting levels. When only headlamps were used and overhead lighting was off, visibility was confined to the limits of the vehicle headlamps. Adding overhead lighting increased the probability of detecting objects off-axis or from distances beyond the reach of the vehicle’s headlamps.

The combination of headlamps and overhead lighting appears to have its greatest impact when the two sources contribute nearly equal amounts of lighting. This requires the object to be within the area illuminated by the vehicle’s headlamps, approximately 91 m (300 ft) for the vehicles used in this study. When headlamps and overhead lighting were combined, detail recognition increased because multiple sources of light illuminated the object from different angles.

The effects of visibility caused by the combination of headlamps and overhead lighting depend on ambient luminance and contrast. High ambient luminance causes objects in positive contrast to be more difficult to detect, and low ambient luminance causes negatively contrasted objects to be more difficult to detect. Also, the extent of ambient luminance’s impact on visibility depends on the amount of luminance contrast between object and background; for example, concrete surfaces reflect more light than asphalt and result in a higher ambient luminance. These results highlighted the complex relationship between ambient luminance, contrast, and visibility. Future research should consider additional factors, such as the impact of headlamps and overhead lighting on object visibility from different vehicle types, with and without oncoming vehicles, in different road profiles, and in twilight conditions.

Applicability of Mesopic Models to the Driving Environment

The CIE Recommended System for Mesopic Photometry accurately predicted the mesopic luminances and contrasts for both the LED light sources but not for HPS lighting. The change in the calculated difference to the predicted difference between the mesopic and the photopic luminances of HPS lighting and both LED overhead-lighting sources indicated that the calculated differences closely followed the predicted differences from 0.07 to 0.2 cd/m2 (0.020 to 0.06 fL). Above that luminance value, the calculated differences leveled off while the predicted values continued to decrease. An ideal mesopic model should also have the eccentricity as an input to accurately calculate mesopic luminances.

Impact of MPI System on Driver Visual Performance

The MPI system did not improve the detection distance of off-axis pedestrians but did improve the rate at which they were detected. Also, participants detected pedestrians from the greatest distances when the MPI system was off. This was the case for sections of the road with and without overhead lighting. This could be because the MPI system’s moving beam distracted the participants and prevented them from scanning normally. Lastly, participants seemed to assume the MPI system would accurately illuminate pedestrians. They detected the pedestrian about 70to 80 percent of the time with the MPI system illuminating the pedestrian, compared with about 50 to 60 percent of the time with the MPI system illuminating the roadway opposite the pedestrian position rather than illuminating the pedestrian.

Additional Findings

Pedestrian clothing color and target color both significantly affected detection and color-recognition distances, whether or not overhead lighting was used.

Object size, ambient lighting level, and contrast affected the visibility of pedestrians and targets in this experiment. The larger an object, the more visible it was, as shown by the VL calculations; pedestrians had higher VLs than targets.

Speed appeared to affect driver attention and gaze patterns, and detection distances increased with speed. When the vehicle was traveling faster, it appeared that the driver focused more on the roadway ahead and glanced less to the side of the roadway.

Distant objects were more visible without headlamps than with headlamps, likely because the headlamp light caused the eye to adapt to the brighter environment. The pool of light in front of the driver made by the headlamps has an impact on the adaptation luminance of the driver. The other results of the experiment show that a higher adaptation luminance required a higher threshold contrast. Distant objects that typically have low contrast would be harder to detect with higher adaptation luminance from the headlamps.


With overhead lighting systems and standard headlamps, the design of higher speed roads need not consider spectral effects because the gaze behavior of a driver cannot be controlled in a real-world driving situation.

Mesopic factors should be applied for low-speed roadways where lighting is designed to provide more benefit to pedestrians than drivers.

Significant effort in the detection and warning methods for the MPI system require significant effort and regulation. While the system shows promise, care must be taken to ensure that negative outcomes are not encountered.

Future Research

The results of this project are limited by the conditions tested. These tests were for drivers in vehicles only. Additional testing to study the application of mesopic factors should be investigated for pedestrians and slower-moving roadway users.

The other aspect noted in these results is the applicability of the mesopic model in a variety of conditions with objects at various eccentricities to the roadway. The relationship of these results to the mesopic model shows that an eccentricity factor may apply to the model and should be investigated further.



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