Inattentional Blindness: Why Drivers May Fail to See Motorcycles in Plain Sight

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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.

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 into its path.
 
Pammer, a professor of psychology and the associate dean of science at Australian National University, notes, “When we are driving, there is a huge amount of sensory information that our brain must deal with. We can’t attend to everything, because this would consume enormous cognitive resources and take too much time. So our brain has to decide what information is most important. The frequency of LBFTS crashes suggests to us a connection with how the brain filters out information.”

Read more at Human Factors and Ergonomics Society

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