Identification of Real-Time Diagnostic Measures of Visual Distraction With an Automatic Eye-Tracking System

Objective: This study was conducted to identify eye glance measures that are diagnostic of visual distraction. Background: Visual distraction degrades performance, but real-time diagnostic measures have not been identified. Method: In a driving simulator, 14 participants responded to a lead vehicle braking at -2 or -2.7 m/s2 periodically while reading a varying number of words (6-15 words every 13 s) on peripheral displays (with diagonal eccentricities of 24°, 43°, and 75°). Results: As the number of words and display eccentricity increased, total glance duration and reaction time increased and driving performance suffered. Conclusion: Correlation coefficients between several glance measures and reaction time or performance variables were reliably high, indicating that these glance measures are diagnostic of visual distraction. It is predicted that for every 25% increase in total glance duration, reaction time is increased by 0.39 s and standard deviation of lane position is increased by 0.06 m. Application: Potential applications of this research include assessing visual distraction in real time, delivering advisories to distracted drivers to reorient their attention to driving, and using distraction information to adapt forward collision and lane departure warning systems to enhance system effectiveness.

[1]  Heikki Summala,et al.  DETECTION THRESHOLDS IN CAR FOLLOWING SITUATIONS AND PERIPHERAL VISION: IMPLICATIONS FOR POSITIONING OF VISUALLY DEMANDING IN-CAR DISPLAYS , 1999 .

[2]  Michael A. Shulman,et al.  Third Annual Report of the Crash Avoidance Metrics Partnership,April 2003 - March 2004 , 2005 .

[3]  Daniel V. McGehee,et al.  Collision Warning Timing, Driver Distraction, and Driver Response to Imminent Rear-End Collisions in a High-Fidelity Driving Simulator , 2002, Hum. Factors.

[4]  Helmut T. Zwahlen,et al.  Safety Aspects of Sophisticated In-Vehicle Information Displays and Controls , 1986 .

[5]  Paul Green,et al.  Driver Distraction, Telematics Design, and Workload Managers: Safety Issues and Solutions , 2004 .

[6]  Philip K. Hughes,et al.  The Effect of Attentional Demand in Eye Movement Behaviour when Driving , 1988 .

[7]  O Laya,et al.  DRIVER'S VISUAL SEARCH IN A FIELD SITUATION AND IN A DRIVING SIMULATOR , 1998 .

[8]  Michael J. Goodman,et al.  Individual Differences and in-Vehicle Distraction While Driving: A Test Track Study and Psychometric Evaluation , 1999 .

[9]  Thomas A. Dingus,et al.  Driver Performance Results from the Travtek IVHS Camera Car Evaluation Study , 1994 .

[10]  John D. Lee,et al.  Preface to the Special Section on Driver Distraction , 2004, Hum. Factors.

[11]  Frank Schieber,et al.  Precision and Accuracy of Video-Based Measurements of Driver's Gaze Location , 1997 .

[12]  Walter W. Wierwille,et al.  An initial model of visual sampling of in-car displays and controls , 1993 .

[13]  Paul Green,et al.  THE 15-SECOND RULE FOR DRIVER INFORMATION SYSTEMS , 1999 .

[14]  Colin M. Macleod.  Half a century of research on the Stroop effect: an integrative review. , 1991, Psychological bulletin.

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

[16]  K Close,et al.  AMERICAN ASSOCIATION OF STATE HIGHWAY AND TRANSPORTATION OFFICIALS COMPUTER SYSTEMS INDEX , 1976 .

[17]  Christopher D. Wickens,et al.  Driving and Side Task Performance: The Effects of Display Clutter, Separation, and Modality , 2004, Hum. Factors.

[18]  Louis Tijerina,et al.  Using Cellular Telephones in Vehicles: Safe or Unsafe? , 1999 .

[19]  Christopher D. Wickens,et al.  An introduction to human factors engineering , 1997 .

[20]  John A. Michon,et al.  Generic intelligent drive support , 1993 .

[21]  J. Theeuwes.  Exogenous and endogenous control of attention: The effect of visual onsets and offsets , 1991, Perception & psychophysics.

[22]  Michael J. Goodman,et al.  The role of driver inattention in crashes: new statistics from the 1995 crashworthiness data system , 1996 .

[23]  Erwin R. Boer,et al.  Development of a steering entropy method for evaluating driver workload , 1999 .

[24]  Louis Tijerina,et al.  HEAVY VEHICLE DRIVER WORKLOAD ASSESSMENT. TASK 7A, IN-CAB TEXT MESSAGE SYSTEM AND CELLULAR PHONE USE BY HEAVY VEHICLE DRIVERS ON ROAD , 1996 .

[25]  P. Hancock,et al.  Human Mental Workload , 1988 .

[26]  I. Brown,et al.  Vision in Vehicles III , 1991 .

[27]  Timothy L. Brown,et al.  Speech-Based Interaction with In-Vehicle Computers: The Effect of Speech-Based E-Mail on Drivers' Attention to the Roadway , 2001, Hum. Factors.

[28]  Christoph Mayser,et al.  REDUCING DRIVERS' MENTAL WORKLOAD BY MEANS OF AN ADAPTIVE MAN-MACHINE INTERFACE , 2003 .

[29]  T H Rockwell,et al.  Spare Visual Capacity in Driving-Revisited: New Empirical Results for an Old Idea , 1988 .

[30]  M. A. Recarte,et al.  Effects of verbal and spatial-imagery tasks on eye fixations while driving. , 2000 .

[31]  Charles C. Adams,et al.  Safety Aspects of CRT Touch Panel Controls in Automobiles , 1988 .

[32]  Naoyuki Osaka.  EFFECTS OF WINDOW SIZE AND ECCENTRICITY UPON EYE FIXATION AND REACTION TIME IN NEGOTIATION OF CURVES. , 1991 .

[33]  David L. Strayer,et al.  Driven to Distraction: Dual-Task Studies of Simulated Driving and Conversing on a Cellular Telephone , 2001, Psychological science.

[34]  Omer Tsimhoni.  VISUAL DEMAND OF DRIVING CURVES AS DETERMINED BY VISUAL OCCLUSION , 1999 .

[35]  John W. Senders,et al.  THE ATTENTIONAL DEMAND OF AUTOMOBILE DRIVING , 1967 .

[36]  Alex M. Andrew,et al.  Humans and Automation: System Design and Research Issues , 2003 .

[37]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .