↓ Skip to main content

Change detection in urban and rural driving scenes: Effects of target type and safety relevance on change blindness

Overview of attention for article published in Accident Analysis & Prevention, January 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 X users

Readers on

mendeley
110 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Title
Change detection in urban and rural driving scenes: Effects of target type and safety relevance on change blindness
Published in
Accident Analysis & Prevention, January 2017
DOI 10.1016/j.aap.2017.01.011
Pubmed ID
Authors
Abstract

The ability to detect changes is crucial for safe driving. Previous research has demonstrated that drivers often experience change blindness, which refers to failed or delayed change detection. The current study explored how susceptibility to change blindness varies as a function of the driving environment, type of object changed, and safety relevance of the change. Twenty-six fully-licenced drivers completed a driving-related change detection task. Changes occurred to seven target objects (road signs, cars, motorcycles, traffic lights, pedestrians, animals, or roadside trees) across two environments (urban or rural). The contextual safety relevance of the change was systematically manipulated within each object category, ranging from high safety relevance (i.e., requiring a response by the driver) to low safety relevance (i.e., requiring no response). When viewing rural scenes, compared with urban scenes, participants were significantly faster and more accurate at detecting changes, and were less susceptible to "looked-but-failed-to-see" errors. Interestingly, safety relevance of the change differentially affected performance in urban and rural environments. In urban scenes, participants were more efficient at detecting changes with higher safety relevance, whereas in rural scenes the effect of safety relevance has marginal to no effect on change detection. Finally, even after accounting for safety relevance, change blindness varied significantly between target types. Overall the results suggest that drivers are less susceptible to change blindness for objects that are likely to change or move (e.g., traffic lights vs. road signs), and for moving objects that pose greater danger (e.g., wild animals vs. pedestrians).

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 110 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 18 16%
Student > Bachelor 14 13%
Researcher 14 13%
Student > Ph. D. Student 10 9%
Other 6 5%
Other 17 15%
Unknown 31 28%
Readers by discipline
Readers by discipline Count As %
Psychology 28 25%
Engineering 23 21%
Computer Science 8 7%
Social Sciences 5 5%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 9 8%
Unknown 35 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2017.
All research outputs
#15,860,480
of 27,515,430 outputs
Outputs from Accident Analysis & Prevention
#2,459
of 4,292 outputs
Outputs of similar age
#219,034
of 429,231 outputs
Outputs of similar age from Accident Analysis & Prevention
#24
of 43 outputs
Altmetric has tracked 27,515,430 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,292 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 429,231 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.