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We’re Only Human

Adding context to accidents using a human-factors analysis

November 23, 2020 Photo

Motor vehicle crashes are often the result of an omission—a missed cue by a driver that leads to an unfortunate outcome. That is why bewildered drivers often say “I didn’t see him” when they deal with the consequences of a mistake on the road.

Post-accident, that quartet of words challenges an attorney tasked with mounting a defense for a driver charged with a crash because juries are often unsympathetic to someone who makes what would appear to be a glaring error that causes injuries and property damage. To the jury, it is hard to understand how a driver could overlook an obvious hazard if he was paying attention. Despite the difficulties defending an at-fault client, science, in the form of a human-factors analysis, offers insight into how someone can make such an error despite being a vigilant driver.

In a standard accident reconstruction, the investigating engineer will recreate the crash from the point of view of the driver, and will account for obvious visual obstructions. A human-factors expert will expand that perspective to include the scene’s sights, sounds, and surroundings, as well as the driver’s mental state and activities, because a driver-failure investigation requires a comprehensive understanding of the pre-crash situation in order to determine when the driver first could have reasonably detected the event.


The initial task in a human-factors analysis is identifying the driver’s expectations en route: Would a typical driver reasonably expect that something specific, like someone walking along the roadside, could happen? Clearly, if the vehicle passes through a residential zone, then it is appropriate to assume that children are present and prone to unpredictable behavior. Alert travelers in the vicinity know to expect darting kids, heavy school-time traffic, and bicycles. On the other hand, if a vehicle travels a remote country road at night, then it is reasonable to assume that a dark-clothed pedestrian will not be walking along the edge of the road. Vigilant drivers will respect the constraints of diminished visibility and travel within lane boundaries, but they do not expect to slow down to the point where a lone walker would be detected early enough to be avoided. 

Societal norms also play roles here. In nations like The Netherlands, where bicycle riders share the road with motor vehicles, drivers expect to see bicycle traffic, and they watch for it. In the U.S., drivers may know that bicycles and motorcycles use the roadways, but they expect episodic encounters, not routine two-wheeled traffic. Ultimately, driver expectation is rooted both in driving savvy and broader cultural patterns.

Detection, Perception, Reaction

From understanding the driving context and the driver’s readiness to react, the human-factors specialist will seek to determine when the driver first detected the problem and recognized that action was needed. Concomitantly, the specialist will also determine when the driver could have detected the problem. For this, the specialist will look at the effects of external elements like time of day, climate/weather, visibility, and location; and then examine those factors that depend on the driver’s familiarity with the location as well as those related to the driver’s perceptual, physical, and cognitive ability. A driver’s acuity, contrast sensitivity, and overall response time deteriorate with age. Alcohol or drug intoxication may also be contributing factors. Especially in complex accident scenes, these driver-specific contributions can make a big difference in the ability to detect a potential risk and react appropriately.

Key to detecting an imminent threat is contrast sensitivity. A salient object—one that stands out from its background—will catch the eye more than a dark object against a dark background or a light object against a light background. Several circumstances decrease an object’s saliency. Bright lights caused by sunlight or headlights shining into the driver’s eyes cause pupil contraction and scatter light in the eyeballs. Both decrease the perceived contrast of objects elsewhere in the scene. Visual clutter and other distractions on the roadways also reduce the chances of catching the driver’s attention.

Perception becomes the lens through which the driver views the world he travels. Human-factors specialists look to two processing modes to describe how a driver will identify a threat. “Bottom/Up Attention” is the processing of salient information as it draws the driver’s attention. A running child with a bright backpack, a large yellow bus stopped in the lane, or lots of people crossing the roadway will draw attention and prompt a driver to slow down in the face of perceived threats. By contrast, “Top/Down Attention” uses contextual information to recognize patterns: “I’m in a school zone so I should expect hazards if I travel during school hours.” Cognition fires up driver vigilance in this case and directs attention to potential risks, such as open gates from which kids could emerge, crosswalks where pedestrians are more likely to be present, and vehicle doors that could swing open.

Experienced drivers know where to put their attention, which is why older drivers with diminished skills can be safer than younger ones with excellent reactions but immature driving abilities. For example, elderly drivers may select routes they know very well so they are familiar with the potential hazards, like blind driveways, children’s play zones, and lurking potholes.

Then there is the physical act of reacting to the threat. That time interval from the event happening (a lead car braking or pedestrian stepping into the roadway, for example) to engaging the brakes is assumed to be 1.5 seconds, but can be as quick as a half-second for the anticipating driver, or stretch to several seconds for an unsuspecting driver.

Case Study

In a recent case that illustrates the impact a human-factors analysis can have on a favorable resolution of fault attribution, an accident occurred on a clear early-morning drive on a two-lane road through a rural setting in proximity to tilled fields. The driver, a 76-year old woman, followed a slight leftward curve of the road and faced a bright blue sky and strong glare from a rising sun on the horizon. Her visor was down to provide relief from the intense light and she was slowing down, estimated to 20 mph, in anticipation of a stop sign at the approaching crossroad. Tall trees in full foliage to her right cast broken shade across her lane of travel. She did not see a farm tractor-trailer towing a spray tank in the deep shade of her lane, entirely to the right of her line-of-sight to the upcoming intersection. The elderly driver rear ended the vehicle causing substantial damage and injuring the tractor-trailer driver.

The tractor-trailer was heading in the same direction as the elderly driver, but on the right-most edge of the lane as he too headed to the stop sign. He was traveling at a moderate rate and was also slowing down in anticipation of the stop at the crossroad. The trailer that held the tank did not have a red retro-reflective triangle or any other reflective device to attract the attention of following traffic.

A human-factors specialist was brought in to study the tractor’s visibility issues and whether or not the at-fault client could have missed seeing the tractor with its bulky white spray tank in tow. Starting with the driver’s expectations, the investigator noted that she was familiar with the road and vehicle types she would encounter en route. Other than coping with the brightness of the day and the dark shadows thrown by the mature trees on the roadside, there were no other weather or climate issues in play. Her age was certainly a factor because contrast sensitivity diminishes with age and disability glare. The driver was challenged to distinguish details ahead of her in the shadows when her visual field was bisected by zones of brightness to her left and deep shadows to her right. Intense light in the background from the sun or a bright skyline reduces visibility, especially for older drivers, who take longer to recover from glare’s consequences. The intense blast of light floods receptors in the eyes and shrinks the pupils, adversely impacting the driver’s ability to distinguish details ahead on the roadway, especially in those dark areas. 

The human-factors specialist made a site visit and took inventory of the accident scene, which supplemented the photos and documentation collected post-crash. With the data in hand, he turned to established resources to gauge the angle of the sun at the exact day/time/location and its relationship to the vehicle positions. When he correlated the sun data with the architecture of the roadway, he noted that there were areas where the tree cover created deep shade that could camouflage a vehicle, especially when the forward view of a following driver was affected by intense sunlight. He noted that the placement of the tractor-trailer to the right edge of the lane slanted away from the elderly driver’s line of sight because the road started veering slightly leftward near the impact site.

At this point in the analysis, the human-factors specialist addressed the question of whether or not the elderly driver could have detected the tractor-trailer as it traveled the road ahead of her. Detection depends on contrast, or the brightness difference between the target (the tractor) and the background (the road surface and shaded trees), relative to the brightness of the background. When he examined the images from the crash site, he noted that the tractor-trailer, even with its whitish plastic tank, faded into the shadows cast by the trees, and it was difficult to distinguish the vehicles from the heavy foliage and the road surface. What the farm vehicle and its trailer lacked, and sorely needed to improve visibility, was the state-mandated slow-moving vehicle reflective triangle. In fact, after doing visibility calculations, the specialist determined that placement of the triangle in those exact same circumstances would have improved the tractor-trailer’s detectability by a factor of five, even with the glare issues that affected the elderly driver. The claim resolved in favor of the defendant.

It is inescapable that a human element contributes to almost every motor vehicle accident, but that does not mean that an omission, oversight, or poor decision is the immediate, or even the overriding, factor leading to a crash. There can be any number of reasons why the driver missed vital clues, and it is the human-factors specialist who offers a detective’s perspective on the degree to which the driver’s detection, perception, and reactions played a role in causing the crash.

About The Authors
Multiple Contributors
Erwin R. Boer

Erwin R. Boer, Ph.D., is a human-factors specialist at Peter R. Thom and Associates Inc. robotentropy@gmail.comrobotentropy@gmail.com

Brad Nelson

Brad Nelson is managing engineer at Peter R. Thom and Associates Inc.  engineering@prtassoc.com

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