Pedestrian fatalities account for approximately 15% of all motor vehicle accident related deaths, and more than half occur at night when visibility is reduced. So, when we as accident reconstructionists are asked to determine whether a typical driver could have avoided striking a particular pedestrian, we usually have to conduct a night-time visibility assessment where we are tasked with re-creating a very close approximation of the visibility conditions at the time of the incident. Reconstructing night-time visibility is a complicated art, but it can be approached in a scientific manner by a forensic expert. A visibility assessment is a pre-requisite to making conclusions about whether a collision with a pedestrian could have been avoidable.

Replicating Conditions

Reconstructing what the driver would have seen requires replicating all (or as many as possible) of the following:

  1. Time of night
    • We have to attend the incident scene at a similar time of night (at, near, or after civil, nautical, or astronomical twilight)
  2. Weather conditions
    • We attend the scene in weather conditions as similar as possible to those at the time of the incident (clear skies, overcast, rain, snow, etc.)
  3. Vehicle Lights
    • We use a similar vehicle or one equipped with exemplar headlamps similar to the one involved in the incident (to ensure proper consideration of the effects of the headlamp type, height, and output)
  4. Pedestrian
    • We use a pedestrian test subject or dummy wearing similar colour and reflectivity of clothing as the pedestrian that was struck during the incident in question
  5. Background & other considerations
    • As much as practically possible, we need to replicate the background of the scene that the pedestrian would have been viewed against, including lights from oncoming vehicles if applicable.

Once at the scene, at the right time of night and in the right conditions, and replicating all of the above, we can begin scientifically measuring visibility.

All of these factors play an important role in our visibility assessments, as they directly determine the contrast of the pedestrian against his/her background.

Measuring Visibility

In general terms, we see via contrast, which is the difference in brightness, colour, or texture between an object and its background. Contrast helps us to discern objects (see Figure 1 below). At night, the ability to discern objects is most dependent on the differences in brightness.


Figure 1: Contrast helps us discern objects. The diamond shape is easier to see in the left two boxes because of the high contrast (difference in brightness) between the diamond and the background. In the two boxes on the right, the brightness of the diamond shape is not as different from the background brightness, and is harder to discern.

After darkness falls, drivers can only see pedestrians by the light that the pedestrians reflect from sources such as headlights, streetlights, etc. But it’s not just the brightness of the pedestrian that matters here; rather, it is the brightness of the pedestrian relative to the background that they are being viewed against (see Figure 2 below). So, when assessing a scene, not only do we have to measure the brightness of a test pedestrian (dressed in clothing as similar as possible to the pedestrian involved in the real-life incident), but also the background.

Figure 2:
Illustration of an observer’s view of the target and background.

There are different tools and methods by which we can measure brightness, but generally, we take luminance measurements of the background and the test-pedestrian, and illuminance measurements of the general collision area. Luminance is just a fancy term for the amount of light reflected back from a particular area (in units of cd/m2). We also measure the amount of light falling on a particular area by taking illuminance measurements (measured in lux). While they sound similar, illuminance is different from luminance. Illuminance is simply the measure of how well lit an area is. If the area is relatively well lit (such as in the downtown area of a large city), there will be more light falling on the pedestrian, which means the pedestrian will be reflecting more light. If the area is poorly lit (such as on a rural country road), there will be little light for the pedestrian to reflect. As such, the headlights and light output from the vehicle is an even more important factor while doing assessments in rural areas (more information on this can be found in an earlier blog post, titled “Headlight Technologies & Accident Reconstruction”).

We take all of these measurements in order to scientifically determine the difference in brightness between the pedestrian and the background; when the difference is high, there is high contrast, which means the pedestrian is more discernible. If the difference is small, the contrast is poor, which means it is difficult to discern the pedestrian. The figures below (taken from Olson) show how the positioning of the pedestrian with respect to the street lights affects the contrast, and correspondingly, how easy it is to discern the pedestrian.

olson photograph examples of contrast
Figure 3:
Examples of contrast – when pedestrian is standing in a lighted area (left), and when pedestrian is standing in a dark area (right). Note: images taken from Olson et. al’s Forensic Aspects of Driver Perception and Response (more details in references below).

There are many factors we always keep mind when taking measurements at the scene. The background against which the pedestrian is being viewed is affected by the time of night, lighting, as well as the weather conditions. Rain generally decreases visibility, as road surfaces become darker when wet. Water can reduce the reflectivity of most clothing, making dark clad pedestrians appear even darker. Rain falling on a windshield (and the movement of the windshield wipers) reduces visibility. If there were oncoming vehicles at the time of the collision, this needs to be accounted for in our visibility tests because increased glare from oncoming vehicles’ headlights can reduce a driver’s ability to see or discern unexpected pedestrians.

Taking Representative Photographs

While conducting night-time visibility assessments, we carefully take photographs that best represent what our eyes saw at the time of the study, and give a general idea as to the lighting of the collision scene. A contrast board (a board painted with several squares, each a different shade of grey) can be used to assess which photographs best represent visibility at the scene. However, the camera is not a human eye and thus the photographs cannot depict exactly what the human eye could have seen, due to camera, display and printing parameters. At best, the photographs captured by the camera, in which the focal length, shutter speed, aperture and light sensitivity settings can be varied by the reconstructionist act as a rough guide of what the reconstructionist actually saw at the time of the tests, as in these examples from actual night-time visibility assessments:

Figure 4:
Examples of night-time visibility assessment photographs. 

Determining Visibility and Detection Distances

Our final task at the scene is to determine when a pedestrian would have first become visible. On a closed road, the investigator actively looks for the test pedestrian while moving the vehicle forward slowly until the pedestrian is discernible. This test is done repeatedly and from different distances for a reliable result. The resulting visibility distance is of course not representative of when a typical driver would have detected the pedestrian, as it has been determined by an investigator who is driving very slowly and actively looking for a pedestrian. However, this visibility distance is typically adjusted to determine the detection distance for a typical driver. Based on some research, the detection distance may be nearly one half or even one third of the visibility distance once you’ve accounted for the fact that a typical driver would not have expected a pedestrian to be there and that they were preoccupied with the task of driving. We use this detection distance in our avoidance analysis (where we determine whether a typical driver could have avoided striking the pedestrian).

To summarize, there are generally four field tasks that we carry out during a night-time visibility assessment: (1) replicating conditions, (2) measuring luminance of the target and background, and illuminance of the general collision area, (3) taking representative photographs, and (4) determining a visibility and detection distances. These four tasks are essential for our assessment of when we would expect a typical driver to first see and potentially detect the pedestrian (or if a typical driver would have been able to see or detect the pedestrian at all – because if there is no detection, the typical response is no response at all). The field tasks we covered here are necessary before we can apply relevant perception-response/ human factors research and analysis to identify whether a typical driver could have avoided striking the pedestrian.


  1. Insurance Institute for Highway Safety (IIHS), “Pedestrians and bicyclists.”
  2. Marc Green et al., Forensic Vision With Application to Highway Safety, Third Edition, Lawyers & Judges Publishing Company, Inc., Tucson, AZ, 2008.
  3. P. Olson, R. Dewar, and E. Farber, Forensic Aspects of Driver Perception and Response, Third Edition, (Tucson, AZ: Lawyers & Judges Publishing Company, Inc., 2010).

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