Considerations when calculating percent road centre from eye movement data in driver distraction monitoring

Percent road center (PRC) is a performance indicator which is sensitive to driver distraction. The original definition of PRC is based on fixation data extracted from eye movement recordings, but it has also been suggested that PRC can be determined directly from the gaze data without segmenting it into saccades and fixations. The primary aim of this paper is to investigate if this is the case. Naturalistic driving data from a small scale field operational test comprising seven vehicles was used in the evaluation. It was found that PRC time traces based on gaze data and fixation data, respectively, were highly similar (correlation coefficient=0.95, average wavelet semblance=0.84) except for an absolute amplitude difference of about 8%. This indicates that the two approaches can be used interchangeably and that the processing step of segmenting gaze data into saccades and fixations can be left out. In addition to this finding, design issues related to the calculation of PRC are investigated. Especially, the impact of gaze cases pointing towards the intersection of the road centre area and the centre rear mirror were investigated. Results lead to conclude that gazes and fixations on the centre rear mirror should be removed from the PRC calculations, as they may negatively influence the correctness of the performance indicator.

[1]  Andrew T. Duchowski,et al.  Eye Tracking Methodology: Theory and Practice , 2003, Springer London.

[2]  Linda Ng Boyle,et al.  The Impact of Distraction Mitigation Strategies on Driving Performance , 2006, Hum. Factors.

[3]  Kenneth W. Gish,et al.  DISTRACTIONS IN EVERYDAY DRIVING , 2003 .

[4]  T. Victor.  Keeping Eye and Mind on the Road , 2005 .

[5]  Ulla Kaisa Knutsson.  SWEDISH NATIONAL ROAD AND TRANSPORT RESEARCH INSTITUTE , 2003 .

[6]  Johan Engström,et al.  Sensitivity of eye-movement measures to in-vehicle task difficulty , 2005 .

[7]  Johan Engström,et al.  Effects of visual and cognitive load in real and simulated motorway driving , 2005 .

[8]  Paul Green.  VISUAL AND TASK DEMANDS OF DRIVER INFORMATION SYSTEMS , 1999 .

[9]  Gordon R. J. Cooper,et al.  Comparing time series using wavelet-based semblance analysis , 2008, Comput. Geosci..

[10]  James R. Sayer,et al.  The Effects of Secondary Tasks on Naturalistic Driving Performance , 2005 .

[11]  Terry C. Lansdown,et al.  AN INVESTIGATION INTO THE UTILITY OF VARIOUS METRICS FOR THE EVALUATION OF DRIVER INFORMATION SYSTEMS , 1998 .

[12]  Thomas A. Dingus,et al.  The Impact of Driver Inattention on Near-Crash/Crash Risk: An Analysis Using the 100-Car Naturalistic Driving Study Data , 2006 .

[13]  M. A. Recarte,et al.  Effects of verbal and spatial-imagery tasks on eye fixations while driving. , 2000, Journal of experimental psychology. Applied.

[14]  Karel Brookhuis,et al.  Issues arising from the HASTE experiments , 2005 .