I am trying to understand whether there is a correlation between how drivers' visual scanning of the road and their behaviour after they encounter a potential collision scenario. I have been working with Percentage Road Centre (PRC; Victor, 2005), but this gives me 5 individual measures. I was wondering if there was some established model, ratio or coefficient to assess the spread of eye fixations within a given time frame.
Thanks in advance!
Victor, T. W. (2005). Keeping eye and mind on the road. Doctoral thesis, Uppsala University, Uppsala.
Hi Tyron,
Our lab has found that the standard deviation of gaze positions provides greater sensitivity than PRC, and is generally simpler to calculate. See the attached pub.
-Jon
Article The sensitivity of different methodologies for characterizin...
Dear Tyron,
I am not sure what you mean with 'the spread of eye fixations' but if you refer to the size / extent of the entire fixated area, you might use principal component analysis (e.g. Oliveira et al 1996).
We are doing different research but have analyzed the size of the total area that children fixated in a given time frame, in degrees of visual angle, as a measure for fixation accuracy (see Pel et al., 2010, J Neurosci Methods).
Good luck!
Marlou Kooiker
Hi Tyron,
Our lab has found that the standard deviation of gaze positions provides greater sensitivity than PRC, and is generally simpler to calculate. See the attached pub.
-Jon
Article The sensitivity of different methodologies for characterizin...
Here is a relevant paper that you may find helpful:
Kircher, K., & Ahlstrom, C. (2010). Predicting Visual Distraction Using Driving Performance Data. Annals of Advances in Automotive Medicine / Annual Scientific Conference, 54, 333–342.
Abstract
Behavioral variables are often used as performance indicators (PIs) of visual or internal distraction induced by secondary tasks. The objective of this study is to investigate whether visual distraction can be predicted by driving performance PIs in a naturalistic setting. Visual distraction is here defined by a gaze based real-time distraction detection algorithm called AttenD. Seven drivers used an instrumented vehicle for one month each in a small scale field operational test. For each of the visual distraction events detected by AttenD, seven PIs such as steering wheel reversal rate and throttle hold were calculated. Corresponding data were also calculated for time periods during which the drivers were classified as attentive. For each PI, means between distracted and attentive states were calculated using t-tests for different time-window sizes (2 – 40 s), and the window width with the smallest resulting p-value was selected as optimal. Based on the optimized PIs, logistic regression was used to predict whether the drivers were attentive or distracted. The logistic regression resulted in predictions which were 76 % correct (sensitivity = 77 % and specificity = 76 %). The conclusion is that there is a relationship between behavioral variables and visual distraction, but the relationship is not strong enough to accurately predict visual driver distraction. Instead, behavioral PIs are probably best suited as complementary to eye tracking based algorithms in order to make them more accurate and robust.
Thanks for your answers, all! I think Jonathan's suggestion of SD of gaze positions best suits our needs.
I think this paper should be relevant here.
PROCEEDINGS of the Fifth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design
CONSIDERATIONS WHEN CALCULATING PERCENT ROAD CENTRE FROM EYE
MOVEMENT DATA IN DRIVER DISTRACTION MONITORING
Christer Ahlstrom, Katja Kircher, Albert Kircher
Swedish National Road and Transport Research Institute (VTI)
Linköping, Sweden
Email: [email protected]
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