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The disproportionately high number of motorcycle-related traffic accidents may be linked to the way the human brain processes—or fails to process—information, according to new research published in Human Factors, "Allocating Attention to Detect Motorcycles: The Role of Inattentional Blindness." The study examines how the phenomenon of inattentional blindness, or a person's failure to notice an unexpected object located in plain sight, might explain the prevalence of looked-but-failed-to-see (LBFTS) crashes, the most common type of collision involving motorcycles.
According to human factors/ergonomics researchers Kristen Pammer, Stephanie Sabadas, and Stephanie Lentern, LBFTS crashes are particularly troublesome because, despite clear conditions and the lack of other hazards or distractions, drivers will look in the direction of the oncoming motorcycle - and in some cases appear to look directly at the motorcycle - but still pull out into its path.
The study authors suggest training drivers to be more alert for motorcycles.
(Score: 2) by RS3 on Saturday January 06 2018, @01:35PM (1 child)
Yes! The human brain, at its most fundamental, is a pattern-matching machine. https://en.wikipedia.org/wiki/Pattern_recognition_(psychology) [wikipedia.org]
We get too used to looking for a car-sized thing. Life is so complex in general, people are generally distracted, thinking about this or that; I perceive at least 1/2 of drivers are doing something on a smartphone while somewhat partially driving. If they look at all, it's a quick glance. Pattern-matcher doesn't see a car, so it's okay to hit gas, and pull out in front of a motorcycle.
(Score: 0) by Anonymous Coward on Saturday January 06 2018, @02:59PM
What's really freaky is when you get it wrong and then the brain realizes that you've gotten it wrong and replaces the image you saw with the correct one.
Around here we have some trees that have weird lumps near the bottom of them. They have the same basic shape as a person with a backpack crouching, so I'll see that, then moments later the image will be replaced with a tree that I was supposed to see.