Category: Uncategorized

By Noah Sabatier

If every installation of an outdoor LED fixture was compared to scoring in sports, the crowd would rise with a resounding cry of “my eyes!”. Of course, LEDs aren’t alone in this issue, nor does any source of light need to produce blinding glare. There is much talk from voices within the lighting industry concerning the goal of minimizing glare. The past decades however have seen a redirection in fixture design with the result of increased glare. A disturbing amount of marketing for lighting, and even some professional research, has appropriated brightness to represent good lighting. This one-dimensional sentiment has been used to market a great deal of visually harsher lighting, under the belief that brighter means better. Unbeknownst to many, glare has come along for the ride.

The alignment of glare and perceived brightness is no mistake. The perception of brightness within human vision is rarely, if ever, an actual representation of objective light levels. Rather it is a feeling of varying discomfort with great subjectivity, in this case it represents the presence of glare. Perceptions of brightness are generally driven by the luminance of a light fixture, dependent on spectrum. In other words, a high-luminance fixture illuminating 100 square feet would be perceived as brighter than a low-luminance fixture illuminating 1000 square feet. To the untrained observer this would result in the first scene being perceived as brighter, and possibly rated as better lighting.

This betrayal of the visual perception system doesn’t end there however, as presented in another hypothetical case. Contrast is a key factor in perceptions of glare and brightness. For example, we have 2 roadways; roadway A is illuminated to 1 candela per square meter (cd/m²) while roadway B is illuminated to 0.3 cd/m². The streetlight fixtures on both roadways A and B have a luminance of 100,000 cd/m² from the position of the viewer. As in the previous scenario, the light fixtures are the highest luminance in the scene and drive perceptions of brightness through glare. Due to the increased contrast between the streetlights and roadway B, the streetlights on roadway B would often be perceived as brighter than those of roadway A. To the untrained observer, this perception will often extend to believing that the overall scene is brighter. This scenario is surprisingly common within the lighting field, where a lamp that puts less light on the ground is perceived as brighter due to lower levels of background luminance.

The previous scenarios may sound odd, so let’s examine the properties of glare. There are two primary types of glare to consider in outdoor lighting. Discomfort glare is a subjective sensation of discomfort caused by light. It is measured on the De Boer scale from ‘barely perceptible’ to ‘intolerable pain’, with a lower De Boer rating representing more glare. Disability glare is an objective measurement of glare, based on the scattering of light within the eye. This scattering creates a wall of light within the eye, physically obstructing vision.

Despite sounding less significant, discomfort glare poses a serious safety risk. Glare-aversion responses, driven by discomfort, result in avoidance of the visual tasks needed to safely navigate an environment. Discomfort glare also results in stress and fatigue due to repeated physical overloading of the brain’s visual system, stress and fatigue being collision factors for drivers. In lesser cases, this makes discomfort glare a general distraction similar to other ‘mild stresses’ such as uncomfortable temperatures. Several factors determine the level of glare that a light fixture produces.

Firstly, shorter wavelengths of light drive stronger reactions of discomfort glare. This spectral dependance of glare has been studied as early as the 1960s for roadway lighting applications. For disability glare, shorter wavelengths of light show a slight increase in glare but overall, there is not a significant dependance on light spectrum. Using longer wavelengths of light, such as yellow or amber, is necessary to minimize discomfort glare.

 

Secondly, the luminance, background contrast and uniformity of a light source drive perceptions of discomfort glare. Great difficulty has been experienced in obtaining consistent results during attempts to quantify discomfort glare. Methods have ranged from subjective ratings such as the De Boer scale, to more objective tests such as pupil response and even brain scans searching for mechanisms of discomfort. With the advent of LEDs and widespread appearance of non-uniform light fixtures, traditional models such as the Unified Glare Rating failed. New studies have been conducted, with unanimous findings that non-uniformity increases discomfort.

Increases in luminance and source size result in greater discomfort glare with some models showing a linear relationship between the 2. Mathematically one may get the misimpression that this makes the size of light sources a non-factor, since lowering luminance while maintaining light output requires a larger source. This is untrue however, as research has shown that diffusing a high-intensity light source into a larger, lower-intensity light source reduces discomfort greatly. For one study, an LED exceeding 1,000,000 cd/m² was diffused to a larger surface area to produce 50,000 cd/m² and then 15,000 cd/m². Despite the illuminance on the subject remaining constant, the LED source became less glaring and more tolerable as it became larger and individual diodes were amalgamated into one source of light.

 

This result echoes the current understanding of discomfort glare in biology and psychology, with the physical overloading of the visual system at multiple levels resulting in discomfort. Of specific importance for the lighting field is that the saturation of cone photoreceptors triggers discomfort. This makes the cone saturation threshold a point of sharp rise in discomfort that many glare models miss. This is possibly because the saturation of cone cells cannot happen under steady light, rather a sudden appearance is required. This complexity is compounded by the situational variance of the cone saturation threshold, based on the pre-exposure adaptation level. Another driver of overall visual discomfort is contrast. Research has found that images containing high-contrast result in discomfort, despite the actual luminance being far below what would be recognized as a glare trigger.

Outdoor area lighting rarely escapes the problem of excessive and uncontrolled luminance. Both HID and LED lamps produce incredible volumes of light from relatively tiny emittance areas, ensuring that unacceptable levels of glare will be produced without a proper fixture. HID fixtures often escaped this issue to some degree through the necessity of large reflectors and lenses, naturally diffusing the lamp’s luminance. While many lighting designers view these mechanisms as an inefficiency, mechanisms of this nature are required to mitigate glare from a light fixture. A variety of designs are possible, but the requirement remains a minimized and uniform luminance level. A business wouldn’t want their customers to walk into (and immediately out of) a sweltering store. In this same regard, lighting designers shouldn’t want their customers to experience visually disturbing levels of glare – even if it means that lamps must be larger and perceived as dimmer.

Noah Sabatier is a photographer and lighting researcher that is dedicated to advocating for better outdoor lighting. Noah has spent the past 5 years living with a night shift sleep schedule, during this time he realized that the streetlights in his city were far from optimal – and recent changes had only made them worse. He has spent the past 2 years extensively reviewing scientific literature and technical documents alongside others advocating for better lighting. Noah is now working to raise awareness of common misconceptions that lead to bad lighting and the better practices needed to solve this problem.

Reach him at: noahsabatierphoto[at]gmail.com

Works Cited:

Teppei KASAHARA, Daisuke AIZAWA, Takashi IRIKURA, Takayoshi MORIYAMA, Masahiro TODA, Masami IWAMOTO, Discomfort Glare Caused by White LED Light Sources, Journal of Light & Visual Environment, 2006, Volume 30, Issue 2, Pages 95-103, Released on J-STAGE October 23, 2006, Online ISSN 1349-8398, Print ISSN 0387-8805, https://doi.org/10.2150/jlve.30.95

Bullough, J., “Luminance versus Luminous Intensity as a Metric for Discomfort Glare,” SAE Technical Paper 2011-01-0111, 2011, https://doi.org/10.4271/2011-01-0111

Dee, P. 2003. The Effect of Spectrum on Discomfort Glare [thesis]. Troy, NY: Rensselaer Polytechnic Institute.

Bullough, JD, Skinner, NP, Pysar, RP, Radetsky, LC, Smith, AM, Rea, MS. 2008a. Nighttime Glare and Driving Performance: Research Findings, DOT HS 811 043. Washington, DC: National Highway Traffic Safety Administration.

Wilkins A. A physiological basis for visual discomfort: Application in lighting design. Lighting Research & Technology. 2016;48(1):44-54. doi:10.1177/1477153515612526

van Bommel, W. (2013). Glare. In: Luo, R. (eds) Encyclopedia of Color Science and Technology. Springer, New York, NY. https://doi.org/10.1007/978-3-642-27851-8_125-3

Steven K. Shevell, Saturation in human cones, Vision Research, Volume 17, Issue 3, 1977, Pages 427-434, ISSN 0042-6989, https://doi.org/10.1016/0042-6989(77)90035-9.

L.M. Geerdinck, J.R. Van Gheluwe, M.C.J.M. Vissenberg, Discomfort glare perception of non-uniform light sources in an office setting, Journal of Environmental Psychology, Volume 39, 2014, Pages 5-13, ISSN 0272-4944, https://doi.org/10.1016/j.jenvp.2014.04.002.

Mesopic Street Lighting Demonstration and Evaluation Final Report for Groton Utilities Groton, Connecticut Prepared by Peter Morante Lighting Research Center Rensselaer Polytechnic Institute Troy, New York

Haigh SM, Barningham L, Berntsen M, Coutts LV, Hobbs ES, Irabor J, Lever EM, Tang P, Wilkins AJ. Discomfort and the cortical haemodynamic response to coloured gratings. Vision Res. 2013 Aug 30;89:47-53. doi: 10.1016/j.visres.2013.07.003. Epub 2013 Jul 15. PMID: 23867567.

Bargary G, Furlan M, Raynham PJ, Barbur JL, Smith AT. Cortical hyperexcitability and sensitivity to discomfort glare. Neuropsychologia. 2015 Mar;69:194-200. doi: 10.1016/j.neuropsychologia.2015.02.006. Epub 2015 Feb 7. PMID: 25659503.

Suzuki Y, Minami T, Laeng B, Nakauchi S. Colorful glares: Effects of colors on brightness illusions measured with pupillometry. Acta Psychol (Amst). 2019 Jul;198:102882. doi: 10.1016/j.actpsy.2019.102882. Epub 2019 Jul 6. PMID: 31288107.

By Noah Sabatier

If you have made it to part 3 of this article series, congratulations! You have now considered more evidence on real-world visual performance than those who decided to install white LED streetlights in your community. If you haven’t, please take a moment to catch up on Part 1 and Part 2 at their respective links. Today we will examine two more factors in lighting selection. Weather and the spectral reflectance of surfaces pose often-overlooked challenges to identifying ideal lighting designs.

In part 1 of this article series, we learned the importance of visual adaptation to light. Visual adaptation relies on the luminance of the environment, something that varies with conditions. The luminance of any surface is based on its spectral reflectance properties. When a solid surface is illuminated, some of that light is absorbed while the rest is reflected. Not only do these reflectance values depend on surface material, but they also vary with the wavelength(s) of light.

Spectral reflectance values are important for understanding two factors of lighting quality that often get left out of lighting guidance. Pavement surfaces such as roadways, parking lots and foot paths have a spectral reflectance that increases with wavelength. This means that, as the wavelength of light increases, more of the light is reflected to produce useful luminance. For example, on an asphalt test surface, 5.38% of light at 450 nanometer (nm) (ie. blue) is reflected. For 580 nm light (yellow), this reflectance value increases to 7.71%. When illuminating a paved outdoor area, less light is needed to produce the same pavement luminance when longer spectrums such as yellow are used.

A much greater difference in spectral reflectance is seen in regions that experience snowy winters. Pavement samples generally offer a spectral reflectance of 5-15% based on material properties and light wavelength. In comparison, the spectral reflectance of fresh snow is generally upwards of 95%. Ice has a lower reflectance of anywhere between 2% and 60+%. These values are deceptively low however, as the mirror-like surfaces often formed by ice produce specular reflections. Rather than light being reflected in a diffuse manner, specular reflection sends light in a single direction. Specular reflection is responsible for seeing an inverted ‘image’ of a light source in a puddle or patch of ice. This image-like reflection results in a luminance hot spot, similar to viewing the light source directly.

The image above shows 3 photographs taken at identical exposure settings in the same location. The photographs have been converted into a scale of relative pixel luminance. The left photo shows regular, dry road conditions. The center photo is taken shortly after rainfall and the right photo shows compacted snow, taken days after a blizzard. The wet road shows a great deal of specular reflectance, resulting in a higher luminance contrast on the surface. Certain regions, such as the puddle, reflect a luminance value close to the light source itself. The winter scene shows greatly increased luminance not only on the road but also on lawns, rooftops and the sky.

A more universal issue for outdoor lighting is that of atmospheric moisture. Water particles fall under Rayleigh scattering, a physics principle that applies to particles smaller than the wavelength of light. The percentage of light affected by Rayleigh scattering is dependent on wavelength, with shorter wavelengths being scattered at higher rates. This can often be seen in foggy conditions and is the reason that fog lights are generally yellow, a relatively long wavelength of visible light. Regions subject to fog will become more hazardous if the wrong spectrum of light is used.

Interactions between light and the environment play a crucial role in implementing quality lighting. Lighting designers must pay attention to the spectral reflectance of the surfaces they’re illuminating, especially if they are using illuminance rather than luminance. Since illuminance is merely a measure of light landing on a surface, it does not account for varying levels of reflectance. This can cause differences in pavement luminance for different spectrums of light, even if lux levels are the same. It is also important for designers to consider local weather patterns in their region. Surfaces subject to regular rain will experience higher levels of luminance contrast while snowy regions will see an overall increase to luminance levels.

Noah Sabatier is a photographer and lighting researcher that is dedicated to advocating for better outdoor lighting. Noah has spent the past 5 years living with a night shift sleep schedule, during this time he realized that the streetlights in his city were far from optimal – and recent changes had only made them worse. He has spent the past 2 years extensively reviewing scientific literature and technical documents alongside others advocating for better lighting. Noah is now working to raise awareness of common misconceptions that lead to bad lighting and the better practices needed to solve this problem.

Reach him at: noahsabatierphoto[at]gmail.com

Works Cited:

Preciado O, Manzano E. Spectral characteristics of road surfaces and eye transmittance: Effects on energy efficiency of road lighting at mesopic levels. Lighting Research & Technology. 2018;50(6):842-861. doi:10.1177/1477153517718227

John Hopkins University Spectral Reflectance Library

https://www.paten-der-nacht.de/lichtverschmutzung-messen/

https://skyandtelescope.org/astronomy-resources/transparency-and-atmospheric-extinction/

A. J. Cox, Alan J. DeWeerd, and Jennifer Linden, “An experiment to measure Mie and Rayleigh total scattering cross sections”, American Journal of Physics 70, 620-625 (2002) https://aapt.scitation.org/doi/10.1119/1.1466815

By Noah Sabatier

In the previous article we discussed how the retina adapts to different levels of light, and what this means for optimizing outdoor dusk-to-dawn lighting. We will now move on to the mechanisms that our visual system uses to aim our eyes. Compared to the rudimentary considerations that luminance adaptation got in professional lighting guidance, there was virtually no examination of eye movements or gaze control. The first major study that tested whether or not roadway lighting guidance was accurate without the aforementioned considerations was conducted in 2015. This is several years after organizations such as the IESNA began to recommend white lighting for general dusk-to-dawn illumination. To put it mildly, the cart was several miles ahead of the horse.

The human visual field is divided into 2 primary sections, focal and peripheral. Recalling from the last article, focal vision is mediated by cone cells while peripheral vision is mediated primarily by rod cells, with a lesser share of cone cells. Focal vision holds precious little area in our visual field, considering the dominant role it plays in visual tasks. The focal region of each eye is only 2 degrees; however, our visual system has a way of expanding this.

Saccadic eye movements subconsciously happen several times per second, rapidly scanning an area of focus to build a larger field of focal vision. Our vision is processed in a way that we do not see the blurred movements, only a final result. There is little consideration for saccadic eye movements in current roadway lighting guidance. This often results in an unrealistic weighting between focal and peripheral vision.

Perhaps more glaring of an issue, reliance on visual performance models for roadway lighting guidance creates an assumption that drivers do not move their eyes or head while driving. In tests conducted for mesopic visual performance models, such as the Unified Photometry System, test subjects did not exhibit natural visual behavior. Instead, test subjects were trained to focus on a central point so that peripheral stimuli are viewed solely through peripheral vision. Based on this artificial reliance upon peripheral vision, bluer spectrums of light found favor for theoretical advantages in rod-cell mediated peripheral vision. Whether this assumption was realistic or not hadn’t been tested before lighting guidance and marketing began to utilize it.

In 2015, the Federal Highway Administration released an extensive research paper on visual performance while driving at night. This 240-page report was based on over a year of testing at a real-world track with full-scale streetlights, vehicles and simulated pedestrians. The final tests conducted for the report were perhaps the most important. The goal of these tests was to measure real world reaction distances under different lighting spectrums, and compare them to model predictions. The results of these tests would have changed the course on white LED lighting implementation worldwide – had those in charge of lighting paid attention.

In the first test, subjects drove down the road while fixating on the centerline. Subjects were specifically instructed to detect peripheral targets without moving their eyes or head to recreate the visual performance model tests. This test found slight, but inconsistent, detection distance advantages for white LED lighting when detecting peripheral targets with a fixed gaze. An additional test found more consistent advantages under white LEDs for the minimum contrast threshold needed to detect peripheral targets with a fixed gaze.

The second test could be described as a natural, real-world experiment. Participants were allowed to behave as they would during normal, every-day driving. This included the freedom to scan the visual field while driving, instead of focusing centrally as was done in laboratory tests. Detection distances under the 3 tested lighting spectrums were surprisingly similar. Consistent increases in detection distance from bluer spectrums of light did not happen until the pedestrian was within the practical extremities of peripheral vision. The results of this test showed a complete failure of the mesopic vision models that are behind streetlight selection guidance.

A more complete picture of visual system operation under artificial lighting is emerging, but a final assumption needs to be tested. Even after the real-world test results revealed a lack of advantages for bluer spectrums of light, there was still a belief that this only applied to faster roadways. It was theorized that slower roadways, specifically those in residential areas, had a higher workload within the peripheral field of drivers. On paper this increased peripheral workload at the lower lighting levels of residential areas created an opportunity for rod cells to provide better vision under shorter wavelengths of light.

A different study was conducted to determine the gaze behaviors of drivers in different environments. Tracking equipment traced both eye and head movements on a main commercial road and a slower residential road. Contrary to the assumption of increased peripheral vision dependance, visual behavior had changed with speed. Drivers took advantage of the lower residential speeds to increase the range of their head and eye movements. These movements allowed drivers to scan a larger area with focal vision. In both the residential and commercial roads, gaze behavior was based on perceived areas of immediate potential conflict. Drivers on the commercial road focused further ahead, down the road itself. Drivers on the residential road consistently glanced to the sides where pedestrians may approach the roadway, as well as vehicles with right-of-way.

We have reached a similar and equally troubling conclusion to that of the previous article on visual adaptation to light. There is a wide gap between the predicted performance of mesopic vision models and that of real-world tests. This gap is largely driven by the failure of mesopic visual performance models to account for the natural eye and head movements of drivers. For example, instead of detecting a pedestrian with peripheral vision at low speeds, drivers would generally find this pedestrian within their focal vision by scanning the road. Under peripheral vision there are advantages for shorter wavelengths of light, but focal vision favors yellow light. This missing factor is the difference between lighting guidance recommending vastly different lighting spectrums. In future articles we will examine environmental factors, glare and ecological impacts.

Noah Sabatier is a photographer and lighting researcher that is dedicated to advocating for better outdoor lighting. Noah has spent the past 5 years living with a night shift sleep schedule, during this time he realized that the streetlights in his city were far from optimal – and recent changes had only made them worse. He has spent the past 2 years extensively reviewing scientific literature and technical documents alongside others advocating for better lighting. Noah is now working to raise awareness of common misconceptions that lead to bad lighting and the better practices needed to solve this problem.

Reach him at: noahsabatierphoto[at]gmail.com

Works Cited:

Winter J, Fotios S, Völker S. Gaze direction when driving after dark on main and residential roads: Where is the dominant location? Lighting Research & Technology. 2017;49(5):574-585. doi:10.1177/1477153516632867

Gibbons, Ronald B. ;Meyer, Jason E.; Terry, Travis N.; Bhagavathula, Rajaram; Lewis, Alan; Flanagan, Michael; Connell, Caroline; Evaluation of the Impact of Spectral Power Distribution on Driver Performance; Virginia Tech Transportation Institute, United States. Federal Highway Administration. Office of Safety Research and Development Report Number : FHWA-HRT-15-047

Rea M, Bullough J, Freyssinier-Nova J, Bierman A. A proposed unified system of photometry. Lighting Research & Technology. 2004;36(2):85-109

Goodman T, Forbes A, Walkey H, et al. Mesopic visual efficiency IV: a model with relevance to nighttime driving and other applications. Lighting Research & Technology. 2007;39(4):365-392.

Bommel, W. Road Lighting. Fundamentals, Technology and Application; Springer: Berlin/Heidelberg, Germany, 2015. Doi: 10.1007/978-3-319-11466-8

By Noah Sabatier

Changing a light bulb in our home is perhaps the most simple task in which we can still credit ourselves for performing household maintenance. The amount of thought such an operation receives rarely extends beyond looking for the most efficient pack of bulbs on a store shelf. What happens however, when a municipal utility department has over 100,000 streetlights to change? 

The ideal dusk-to-dawn area light is often defined by lamp efficacy, while lamp efficacy is defined by the operating parameters of human vision. These parameters of human vision are defined by a series of laboratory tests, looking to answer a seemingly simple question – what spectrum of light enables the highest efficacy for vision on a roadway at night?

Depending on where you live, a lighting standards organization such as the CIE (Commission Internationale de l’Eclairage or International Commission on Illumination) or IESNA (Illuminating Engineering Society of North America more often called the IES) has provided your municipality with documents to answer this question. To simplify this exchange of information, a few assumptions have been made; While roadways are illuminated, streetlights themselves are not visible. As a driver neither you nor your fellow road user drives with headlights at night, nor do you ever turn your head or move your gaze throughout the road. If this scenario sounds odd, you aren’t the only one wondering how billions of dollars were invested based on lighting specifications following these assumptions.

During the 1990s, sources of ‘white’ lighting such as metal halide and magnetic induction were raised as alternatives to the industry standard high-pressure sodium lamp. What millions of people simply knew as ‘the yellow streetlights’ were in operation for that exact reason. Yellow is the most efficient portion of visible light for human vision, at least during daytime hours. To understand lighting research, one needs a crash course on human vision:

The human eye contains 2 classes of cells for vision. Cone cells operate in the ‘brighter’, photopic, end of human vision with a peak sensitivity to yellow light. Cone cells are located primarily in the center of the retina, provide sharp ‘focal’ vision and allow us to perceive color. Rod cells operate in the ‘darker’, scotopic, end of human vision with a peak sensitivity to bluish-green light. Rod cells are located primarily in the peripheral region of the retina and provide colorless vision with low resolution. Rod cells require extensive time to generate photopigment in order to achieve sensitivity to light, upwards of 30 minutes for peak sensitivity. It only takes a few seconds, however, for this photopigment to be lost when exposed to bright light. 

The primary research behind standards for roadway lighting is the Mesopic Optimization of Visual Efficiency, shortened to M.O.V.E. – mesopic being the range in which both cone and rod cells are theoretically active. MOVE studies consisted of participants in a laboratory performing simulated visual tasks, generally using test stimuli projected onto a background. At one point a driving simulator was utilized, although this also consisted of a simple series of light projections onto a background.

MOVE studies include 3 primary themes worth considering before their application to the real world. Firstly, subjects were given varying amounts of time in a dark room for their eyes to adapt to the luminance level being tested – up to 30 minutes. Secondly, visual performance tests utilized a fixation point and trained subjects to ensure that peripheral vision was being tested when peripheral stimuli was in use. Finally, subjects were never exposed to luminance levels above that of the test surface, up to 10 candela per square meter.

For those of us who don’t live inside a laboratory simulation, we can only dream of driving in the dark for 30 minutes without being subjected to oncoming headlights and other sources of bright light. When exposure to bright light occurs, a variety of biological processes happen within the eyes to adapt to this light. Firstly, the pupil narrows during the Post-Illumination Pupil Response. Shorter wavelengths of light have a much stronger PIPR impact than longer wavelengths of light, as has been observed in a variety of studies. The increased pupil response to blue light is additionally a trigger for physical discomfort.

After PIPR takes place, a series of reactions happen within and between retinal cells. To summarize, the photopigment within rod cells absorbs light and becomes transparent. Should the photopigment become completely transparent, the rod cell is blind until the pigment can regenerate. Cone cells experience an adaptation process as well, albeit with less sensitivity and a much faster recovery time. We often see this as colored ‘splotches’ within our vision, matching the shape of the light source that we viewed. Getting more complex, retinal cells can also receive adaptation ‘instructions’ from their peers. Specifically, cone cells being exposed to bright light results in rod cells across the retina adapting to the light source, resulting in a full-field reduction of light sensitivity.

When the results of the MOVE studies are placed within the context of visual adaptation mechanics, we can make the following conclusions:

• The theoretical advantage for shorter wavelengths of light in dusk-to-dawn lighting only exists for peripheral vision.
• This theoretical advantage, mediated by rod cells, exists up until 0.6 cd/m². Roadway luminance targets range between 0.3 and 2.0 cd/m².
• When driving at night, drivers are exposed to an onslaught of light sources. The luminance of these light sources are several magnitudes greater than the upper limit for rod cell function. Even cone cells are routinely blinded by bright lights, often leading to temporary full-field night blindness.

With these factors in mind, a troubling conclusion for much of the lighting field emerges. In a real-world scenario, there is no evidence that rod cells are able to reliably contribute to vision under standard artificial illumination. Whether you have been informed of a supposed 30% gain in efficiency, or a whopping 70% provided by increased sensitivity to blue light, there was never a foundation behind these numbers. Without reliable vision from rod cells, we are left with our cone cells that perceive yellow light most efficiently. In the second part of this article we will examine real-world driving tests and see how they compare to the laboratory-based models used to select the streetlights outside your home.

Noah Sabatier is a photographer and lighting researcher that is dedicated to advocating for better outdoor lighting. Noah has spent the past 5 years living with a night shift sleep schedule, during this time he realized that the streetlights in his city were far from optimal – and recent changes had only made them worse. He has spent the past 2 years extensively reviewing scientific literature and technical documents alongside others advocating for better lighting. Noah is now working to raise awareness of common misconceptions that lead to bad lighting and the better practices needed to solve this problem.

Reach him at: noahsabatierphoto[at]gmail.com

Works Cited:

Rea M, Bullough J, Freyssinier-Nova J, Bierman A. A proposed unified system of photometry. Lighting Research & Technology. 2004;36(2):85-109

Goodman T, Forbes A, Walkey H, et al. Mesopic visual efficiency IV: a model with relevance to nighttime driving and other applications. Lighting Research & Technology. 2007;39(4):365-392.

Uchida T, Ayama M, Akashi Y, et al. Adaptation luminance simulation for CIE mesopic photometry system implementation. Lighting Research & Technology. 2016;48(1):14-25

Bommel, W. Road Lighting. Fundamentals, Technology and Application; Springer: Berlin/Heidelberg, Germany, 2015. Doi: 10.1007/978-3-319-11466-8

Sharpe LT, Fach CC, Stockman A. The field adaptation of the human rod visual system. J Physiol. 1992 Jan;445:319-43. doi: 10.1113/jphysiol.1992.sp018926. PMID: 1501137; PMCID: PMC1179984.

Lei, Shaobo & Goltz, Herb & Chandrakumar, Mano & Wong, Agnes. (2014). Full-Field Chromatic Pupillometry for the Assessment of the Post-Illumination Pupil Response Driven by Melanopsin-Containing Retinal Ganglion Cells.. Investigative ophthalmology & visual science. 55. 10.1167/iovs.14-14103.

The Streetlight Effect: Modern Considerations of Early Observations in the Psychology of Outdoor Lighting

By Noah Sabatier

It’s no secret that people don’t enjoy searching for something in the dark. Shadows dance, shapes shift and forms seemingly appear out of nowhere. The Streetlight Effect originated as an early 1900s anecdote in which a drunken man is searching for his keys. A police officer helps him search, resulting in both men spending several minutes under a streetlight. When the officer asks if the drunken man lost his keys under the streetlight he replies “no, this is where the light is”. 

The stakes become much higher while driving, when individuals have mere seconds to see, identify and react to obstacles. This visual ability can be the difference between life and death, as new statistics suggest. 2022 saw a 40-year high of pedestrian deaths in the US, with the trend growing at an alarming rate. Commonly blamed for this rise in pedestrian fatalities is mobile device usage by drivers and the gradual increase in average vehicle size. The statistics paint a different picture however; 

While these statistics don’t reveal the cause of every fatality, we can safely conclude that vehicles do not magically shrink after sunset, nor do mobile devices vanish at night. With such a sharp rise specifically in nighttime fatalities we need to ask; What went wrong with roadway lighting and vehicle headlights?

Research on driver behavior confirms the aforementioned streetlight effect. In 2013 the gaze direction of drivers was examined on a stretch of road during day and night. During daylight hours when sunlight provided illumination of the entire scene, horizontal gaze direction extended beyond either edge of the road. This changed for night driving tests, in which gaze patterns shrunk to match the areas illuminated by headlights and streetlights. There was little to no desire for drivers to spend precious seconds gazing around unlit areas, nor was there a visual stimulus to draw the attention of visual gaze.

 

Further research conducted in 2015 examined the visual behavior of drivers by tracking both their head movements and eye movements to establish gaze direction. 2 roads were utilized for testing, a main route and a residential street both illuminated by streetlights. Collected data revealed that drivers consciously adjust their gaze based on anticipated hazards and vehicle speed. Driving down a main route, the driver’s gaze was narrowed and more time was spent focusing down the road. In the residential area, more time was spent scanning the near side of the road as well as regions where other cars or pedestrians could enter the vehicle’s path.

 

Proper understanding of driver gaze behavior is important, as improper lighting can reduce a driver’s ability to detect targets before they enter the roadway. With the majority of LED fixtures sporting a lower efficacy than the sodium lights they replaced, especially in early transitions, their energy savings relied on illuminating a smaller area to a lower level of luminance. While this is a case-by-case issue for different transitions, common trends can be observed. In many cases the illumination of sidewalks was reduced, both behind and infront of LED streetlights. In fewer cases, dark spots were created between light posts where the LED light was unable to match the illumination area of the previous sodium light fixture. Neither of these are mistakes, as a primary selling feature of LED fixtures is energy savings through tighter illumination patterns.

Understanding both visual psychology and the biological mechanics of the retina is critical to implementing lighting optimally. For an industry and professional field increasingly focused on reducing light pollution, minimizing illuminated areas is often considered a primary goal. Caution must be used however, as research reveals that driver gaze extends beyond the roadway in anticipation of hazards based on the driving scenario.  Should new lighting systems reduce luminance levels on a sidewalk or highway shoulder, drivers may lose their ability to detect hazards before they enter the vehicle’s path. If the goal of visibility and safety is a priority for the lighting field, our gaze must widen to issues of visual system psychology.

Noah Sabatier is a photographer and lighting researcher that is dedicated to advocating for better outdoor lighting. Noah has spent the past 5 years living with a night shift sleep schedule, during this time he realized that the streetlights in his city were far from optimal – and recent changes had only made them worse. He has spent the past 2 years extensively reviewing scientific literature and technical documents alongside others advocating for better lighting. Noah is now working to raise awareness of common misconceptions that lead to bad lighting and the better practices needed to solve this problem.

Works Cited:

Cengiz C, Kotkanen H, Puolakka M, et al. Combined eye-tracking and luminance measurements while driving on a rural road: Towards determining mesopic adaptation luminance. Lighting Research & Technology. 2014;46(6):676-694. doi:10.1177/1477153513503361

Governors Highway Safety Association 2022 Preliminary Data
https://www.ghsa.org/sites/default/files/2023-06/GHSA%20-%20Pedestrian%20Traffic%20Fatalities%20by%20State%2C%202022%20Preliminary%20Data%20%28January-December%29.pdf

Fujiyama, Taku & Childs, Craig & Boampong, Derrick & Tyler, Nick. (2007). How do elderly pedestrians perceive hazards in the street? –

An initial investigation towards development of a pedestrian simulation that incorporates reaction of various pedestrians to environments. Social Research in Transport (SORT) Clearinghouse.

Gibbons, Ronald B.;Meyer, Jason E.;Terry, Travis N.;Bhagavathula, Rajaram;Lewis, Alan;Flanagan, Michael;Connell, Caroline; Evaluation of the Impact of Spectral Power Distribution on Driver Performance; Virginia Tech Transportation Institute, United States. Federal Highway Administration. Office of Safety Research and Development Report Number : FHWA-HRT-15-047

Lighting for the Aging Eye

By Noah Sabatier

In 2022 nearly 1/3rd of the US population was over the age of 55. Many of us personally know someone who has struggled with vision as they age, these challenges becoming most present during driving. This issue is reflected in research, with older drivers displaying slower reaction times and higher collision rates compared to younger drivers. Driving performance differences become amplified at night, a time in which the aging eye has its greatest impact on visibility.

The most visible aspect of the aging eye is a constricted pupil opening. Physically, the pupil is the first means of adaptation to light. As the eye ages, the maximum diameter of the pupil dwindles to half of its former size at a younger age. Consequently we see a loss in the quantity of light that is able to physically reach the retina.

Once a diminished quantity of light enters the pupil, older individuals face another challenge in visibility. Over time the lens of the eye yellows and takes on a cloudy appearance, modifying the spectral transmittance of the lens. Large quantities of blue light are absorbed by the lens, along with some degree of green light. Yellow, amber and red light is largely unaffected by the yellowed lens. When the impacts of a narrowed pupil diameter and yellowed lens are considered, the loss of light transmission is comparable to a young person wearing sunglasses at night.

Spectral transmission of the eye’s lens for ages 50 and 65, relative to age 25.

Within the Mesopic range of vision, in which both Cone cells and Rod cells are mathematically active, the greatest determining factor of visual performance is luminance levels. In the majority of Mesopic visual performance studies, subjects were in their 20s and 30s. This is important to note, as the goal of Mesopic visual performance studies centers around finding the optimum spectrum for lighting, as well as the minimum luminance level needed to achieve a specified level of visibility. Without taking factors of the aging eye into account, we end up with a Mesopic visual performance model that does not represent people of all ages.

Issues with a lack of accounting for age can be seen in the following scenario; Generic Roadway Lighting Guide lists 0.3 cd/m^2 as the appropriate luminance target for a roadway based on its traffic and speed limit. This number is derived from Mesopic visual performance models, in which 0.3 cd/m^2 correlates to factors of visual performance such as reaction time and the ability to discern object details. While younger individuals will experience the predicted level of visual performance, older individuals are left behind. Unable to physically receive the same quantity of light, their visual performance is below that of the intended target. 

A much greater issue brought about in the era of ‘white’ LEDs is that of a shifting spectral sensitivity with age. When the lens of someone aged 50 is compared to that of someone aged 25, the transmission of deep blue light is reduced by over 50%. Cyan transmittance is reduced by ~25%, while losses for yellow light are around 10% or less. In his technical guide, lighting researcher Wout van Bommel calculated the difference in light transmission for someone aged 25 and someone aged 50 under LEDs. The light from a 4000K ‘neutral’ LED was 11% less visible than light from a 2700K ‘warm’ LED. 

If lighting practitioners wish to provide the best visibility possible to individuals of all ages, several considerations need to be made. Older individuals require a higher luminance level in order to achieve the same visual performance as a younger individual. The difference in required luminance levels becomes greater as the short wavelength content of a light source increases. While increasing luminance targets is a contentious issue, especially among light pollution advocates, there is little question as to the ideal spectrum of light sources for older individuals; The yellow-amber spectrum.  Should we desire to reduce accident rates for the most at-risk class of drivers, implementing lighting optimized for all ages is an easy step to take.

Noah Sabatier is a photographer and lighting researcher that is dedicated to advocating for better outdoor lighting. Noah has spent the past 5 years living with a night shift sleep schedule, during this time he realized that the streetlights in his city were far from optimal – and recent changes had only made them worse. He has spent the past 2 years extensively reviewing scientific literature and technical documents alongside others advocating for better lighting. Noah is now working to raise awareness of common misconceptions that lead to bad lighting and the better practices needed to solve this problem.

Works Cited:

https://www.census.gov/data/tables/2022/demo/age-and-sex/2022-older-population.html

Shadi Doroudgar, Hannah Mae Chuang, Paul J. Perry, Kelan Thomas, Kimberly Bohnert & Joanne Canedo (2017) Driving performance comparing older versus younger drivers, Traffic Injury Prevention, 18:1, 41-46, DOI: 10.1080/15389588.2016.1194980

Walkey H, Orreveteläinen P, Barbur J, et al. Mesopic visual efficiency II: reaction time experiments. Lighting Research & Technology. 2007;39(4):335-354. doi:10.1177/1477153507080920

van de Kraats J, van Norren D. Optical density of the aging human ocular media in the visible and the UV. J Opt Soc Am A Opt Image Sci Vis. 2007 Jul;24(7):1842-57. doi: 10.1364/josaa.24.001842. PMID: 17728807.

Preciado O, Manzano E. Spectral characteristics of road surfaces and eye transmittance: Effects on energy efficiency of road lighting at mesopic levels. Lighting Research & Technology. 2018;50(6):842-861. doi:10.1177/1477153517718227

Vicente, E.G., Arranz, I., Issolio, L. et al. Influence of age and spectral power distribution on mesopic visual sensitivity. Atten Percept Psychophys 81, 504–516 (2019). https://doi.org/10.3758/s13414-018-1616-6

Bommel, W. Road Lighting. Fundamentals, Technology and Application; Springer: Berlin/Heidelberg, Germany, 2015. Doi: 10.1007/978-3-319-11466-8