Investigating drivers' visual search strategies : towards an efficient training intervention

Road crashes are the main cause of death of young people in the developed world. The factors that cause traffic crashes are numerous; however, most researchers agree that a lack of driving experience is a major contributing factor. Another reason that has been reported for the increased crashes is that novice drivers have not developed the optimum visual search strategies of their more experienced counterparts. Although several training interventions have tried to improve scanning of novice drivers, they have limited success. The aims of this Thesis are to identify some parameters that influence visual search and to develop an efficient training intervention that will improve drivers’ visual skills. In Experiment 1 an image-based questionnaire was used to assess driving instructors’ and novice drivers’ priority ratings to different areas of the driving scene. Results showed that for both groups the opinions regarding visual field prioritisation were highly consistent when compared to chance. Despite the rating consistencies, group differences were found, across all scenarios with “Rear View Mirrors” being the visual field with the most frequent observed group differences. Certain categories (“Road Ahead” and “Mirrors”) were highly ranked across all scenarios, while other categories were more scenario specific. In Experiments 2 & 3 a novel experimental paradigm was used to investigate the interaction bottom-up and top-down influences upon drivers’ visual attention. Analysis showed that participants’ fixation locations had a stronger relationship with where participants clicked (top down) than with saliency peaks (bottom up). In Experiments 4 & 5 the difference in eye movements between driving instructors and learner drivers was examined during simulated driving. Results showed that driving instructors had an increased sampling rate, shorter processing time and broader scanning of the road than learner drivers. Scenario-specific analysis showed that instructors fixated more than learners on side mirrors while learners showed higher visual allocation to the rear view mirror. It was also found that poor visibility conditions and especially rain decrease the effectiveness of drivers’ visual search. Finally in Experiments 6, 7 & 8 we asked how we can improve learner drivers’ visual skills. Results from Experiments 6 & 7 demonstrated that the ability to distinguish between the eye movements of learner drivers and driving instructors improved as the number of objective differences between the two groups increased across specific scenarios. In Experiment 8 a pilot study showed that a scenario specific training intervention can improve certain aspects of learner drivers’ visual skills. The findings of this Thesis have both theoretical and practical implications regarding drivers’ visual search.

[1]  Pilar Tejero,et al.  Rear-view mirror use, driver alertness and road type: an empirical study using EEG measures , 2006 .

[2]  H. J. Wyatt,et al.  Pupillary light reflex in humans: Evidence for an unbalanced pathway from nasal retina, and for signal cancellation in brainstem , 1981, Vision Research.

[3]  J Toernros,et al.  DRIVING BEHAVIOUR IN A REAL AND A SIMULATED ROAD TUNNEL , 1996 .

[4]  Przemyslaw Rokita,et al.  Simulating Poor Visibility Conditions Using Image Processing , 1997, Real Time Imaging.

[5]  D. S. Wooding,et al.  Automatic control of saccadic eye movements made in visual inspection of briefly presented 2-D images. , 1995, Spatial vision.

[6]  S Plainis,et al.  Reaction times as an index of visual conspicuity when driving at night , 2002, Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians.

[7]  B. Reimer,et al.  Using self-reported data to assess the validity of driving simulation data , 2006, Behavior research methods.

[8]  Christof Koch,et al.  Modeling attention to salient proto-objects , 2006, Neural Networks.

[9]  Leland Wilkinson,et al.  Statistical Methods in Psychology Journals Guidelines and Explanations , 2005 .

[10]  J. C. Johnston,et al.  Attention and performance. , 2001, Annual review of psychology.

[11]  G Underwood,et al.  Visual attention and the transition from novice to advanced driver , 2007, Ergonomics.

[12]  Heikki Summala,et al.  Maintaining Lane Position with Peripheral Vision during In-Vehicle Tasks , 1996, Hum. Factors.

[13]  Alexander Pollatsek,et al.  Using Eye Movements To Evaluate Effects of Driver Age on Risk Perception in a Driving Simulator , 2005, Hum. Factors.

[14]  M. Sarter,et al.  The cognitive neuroscience of sustained attention: where top-down meets bottom-up , 2001, Brain Research Reviews.

[15]  J. Enns,et al.  Paying attention behind the wheel: a framework for studying the role of attention in driving , 2004 .

[16]  David Crundall,et al.  Selective searching while driving: the role of experience in hazard detection and general surveillance , 2002, Ergonomics.

[17]  S. Yantis Stimulus-driven attentional capture and attentional control settings. , 1993, Journal of experimental psychology. Human perception and performance.

[18]  Ronald A. Rensink,et al.  On the Failure to Detect Changes in Scenes Across Brief Interruptions , 2000 .

[19]  D. Whitaker,et al.  Factors affecting light-adapted pupil size in normal human subjects. , 1994, Investigative ophthalmology & visual science.

[20]  Heikki Summala,et al.  Cross-cultural differences in driving skills: a comparison of six countries. , 2006, Accident; analysis and prevention.

[21]  K. Rayner Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[22]  T A Ranney,et al.  Models of driving behavior: a review of their evolution. , 1994, Accident; analysis and prevention.

[23]  M. Hayhoe,et al.  What controls attention in natural environments? , 2001, Vision Research.

[24]  T. Foulsham,et al.  Quarterly Journal of Experimental Psychology: in press Visual saliency and semantic incongruency influence eye movements when , 2022 .

[25]  Allan F Williams,et al.  Teenage drivers: patterns of risk. , 2003, Journal of safety research.

[26]  Matthew P. Reed,et al.  Comparison of driving performance on-road and in a low-cost simulator using a concurrent telephone dialling task , 1999 .

[27]  G. Underwood,et al.  Low-level visual saliency does not predict change detection in natural scenes. , 2007, Journal of vision.

[28]  T. Lajunen,et al.  Driver Behaviour Questionnaire: a follow-up study. , 2006, Accident; analysis and prevention.

[29]  T. Rockwell,et al.  Strategies of visual search by novice and experimental drivers. , 1972, Human factors.

[30]  Sotiris Plainis,et al.  The Role of Retinal Adaptation in Night Driving , 2005, Optometry and vision science : official publication of the American Academy of Optometry.

[31]  Daniel C. Richardson,et al.  Eye Tracking: Characteristics And Methods , 2004 .

[32]  S. Treue Neural correlates of attention in primate visual cortex , 2001, Trends in Neurosciences.

[33]  Derrick J. Parkhurst,et al.  Modeling the role of salience in the allocation of overt visual attention , 2002, Vision Research.

[34]  H. Nothdurft,et al.  Salience and target selection in visual search , 2006 .

[35]  Susan K. Schnipke,et al.  Trials and tribulations of using an eye-tracking system , 2000, CHI Extended Abstracts.

[36]  P M Salmon,et al.  Changing drivers' minds: the evaluation of an advanced driver coaching system , 2007, Ergonomics.

[37]  Daniel R Mayhew,et al.  Driver education and graduated licensing in North America: past, present, and future. , 2007, Journal of safety research.

[38]  Daniel C. Richardson,et al.  Eye Tracking: Characteristics And Methods , 2004 .

[39]  H Summala,et al.  Driving experience and perception of the lead car's braking when looking at in-car targets. , 1998, Accident; analysis and prevention.

[40]  A. L. Yarbus,et al.  Eye Movements and Vision , 1967, Springer US.

[41]  Boris M. Velichkovsky,et al.  Visual Fixations as a Rapid Indicator of Hazard Perception , 2003 .

[42]  Bryan Reimer,et al.  Secondary analysis of time of day on simulated driving performance. , 2007, Journal of safety research.

[43]  L P Noldus,et al.  The Observer Video-Pro: New software for the collection, management, and presentation of time-structured data from videotapes and digital media files , 2000, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.