Identifying the main factors contributing to driving errors and traffic violations - results from naturalistic driving data

Abstract Researchers have identified various factors that likely affect aberrant driving behaviors and therefore crash risk. However, it remains unclear which of these factors poses the greatest risk for either errors or violations under naturalistic driving conditions. This study investigated important variables contributing to driving errors and traffic violations based on naturalistic driving data from the second Strategic Highway Research Program (SHRP 2). In addition, this study identified factors determining the drivers’ willingness to perform common secondary tasks while driving, which have been associated with different degrees of crash risk. Results showed that anger , passenger presence , and persistent individual differences in driver behavior were the main factors associated with committed violations; surprise , high-risk visually distracting secondary tasks , and the driving task demand passing through an interchange were the main factors associated with errors. The willingness to engage in risky secondary tasks while driving appeared to be related to an overall tendency to engage in risky driving behaviors. However, drivers considered the driving context particularly when engaging in visually distracting secondary tasks. This study’s comprehensive approach should be a step towards generating a complete model of the variables that contribute to, or mitigate dangers in traffic.

[1]  Wolfgang Fastenmeier,et al.  Reliability of drivers in urban intersections. , 2010, Accident; analysis and prevention.

[2]  David D Clarke,et al.  Voluntary risk taking and skill deficits in young driver accidents in the UK. , 2005, Accident; analysis and prevention.

[3]  John Sibert,et al.  AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models , 2012, Optim. Methods Softw..

[4]  Tova Rosenbloom,et al.  Tendency to commit traffic violations and presence of passengers in the car , 2016 .

[5]  Christopher D. Wickens,et al.  Examining the Impact of Cell Phone Conversations on Driving Using Meta-Analytic Techniques , 2006, Hum. Factors.

[6]  G Grayson,et al.  Cohort II - A study of learner and new drivers - volume 1 - main report , volume 2 - questionnaires and data tables , 2008 .

[7]  Tom Brijs,et al.  Investigating risky, distracting, and protective peer passenger effects in a dual process framework. , 2016, Accident; analysis and prevention.

[8]  Michael A. Regan,et al.  Driver distraction: A review of the literature , 2003 .

[9]  Marco Dozza,et al.  Analysis of Naturalistic Driving Study Data: Safer Glances, Driver Inattention, and Crash Risk , 2014 .

[10]  Ryan C. Martin,et al.  Driving anger, sensation seeking, impulsiveness, and boredom proneness in the prediction of unsafe driving. , 2005, Accident; analysis and prevention.

[11]  S Stradling,et al.  Errors and violations on the roads: a real distinction? , 1990, Ergonomics.

[12]  Julie McClafferty,et al.  Development of a protocol to classify drivers' emotional conversation , 2017 .

[13]  Myounghoon Jeon,et al.  Effects of specific emotions on subjective judgment, driving performance, and perceived workload , 2014 .

[14]  A. Zuur,et al.  Mixed Effects Models and Extensions in Ecology with R , 2009 .

[15]  David L. Strayer,et al.  Measuring Cognitive Distraction in the Automobile II: Assessing In-Vehicle Voice-Based InteractiveTechnologies , 2014 .

[16]  Lin Qiu,et al.  Effects of Adverse Weather on Traffic Crashes , 2008 .

[17]  Fang Yan,et al.  Cell phone users, reported crash risk, unsafe driving behaviors and dispositions: a survey of motorists in Maryland. , 2007, Journal of safety research.

[18]  Feng Guo,et al.  Driver crash risk factors and prevalence evaluation using naturalistic driving data , 2016, Proceedings of the National Academy of Sciences.

[19]  Daniel V. McGehee,et al.  Using Naturalistic Driving Data toAssess the Prevalence of EnvironmentalFactors and Driver Behaviors in TeenDriver Crashes , 2015 .

[20]  S. West,et al.  The Analysis of Count Data: A Gentle Introduction to Poisson Regression and Its Alternatives , 2009, Journal of personality assessment.

[21]  A. Singhal,et al.  The emotional side of cognitive distraction: Implications for road safety. , 2013, Accident; analysis and prevention.

[22]  Kristie L. Young,et al.  At the cross-roads: an on-road examination of driving errors at intersections. , 2013, Accident; analysis and prevention.

[23]  O Carsten,et al.  Protective or Not , 2015 .

[24]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[25]  Maria Staubach,et al.  Factors correlated with traffic accidents as a basis for evaluating Advanced Driver Assistance Systems. , 2009, Accident; analysis and prevention.

[26]  Kenneth L Campbell The SHRP 2 Naturalistic Driving Study: Addressing Driver Performance and Behavior in Traffic Safety , 2012 .

[27]  H. Summala,et al.  Risky driving and recorded driving offences: a 24-year follow-up study. , 2014, Accident; analysis and prevention.

[28]  Josef F. Krems,et al.  Effects of driving anger on driver behavior – Results from naturalistic driving data ☆ , 2017 .

[29]  Miranda Cornelissen,et al.  Distraction-induced driving error: an on-road examination of the errors made by distracted and undistracted drivers. , 2013, Accident; analysis and prevention.

[30]  R. S. Lynch,et al.  The driving anger expression inventory: a measure of how people express their anger on the road. , 2002, Behaviour research and therapy.

[31]  Craig Bartle,et al.  Young driver accidents in the UK: the influence of age, experience, and time of day. , 2006, Accident; analysis and prevention.

[32]  Manuela Bina,et al.  Risky driving and lifestyles in adolescence. , 2006, Accident; analysis and prevention.

[33]  E. Mulvey,et al.  Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models. , 1995, Psychological bulletin.

[34]  Mark Asbridge,et al.  A meta-analysis of the effects of texting on driving. , 2014, Accident; analysis and prevention.

[35]  Björn Peters,et al.  Driver impairment at night and its relation to physiological sleepiness. , 2008, Scandinavian journal of work, environment & health.

[36]  J. Conger,et al.  Evaluation of cognitive responses to anger-provoking driving situations using the Articulated Thoughts during Simulated Situations procedure , 2011 .

[37]  Yaobin Chen,et al.  Studying the Effects of Driver Distraction and Traffic Density on the Probability of Crash and Near-Crash Events in Naturalistic Driving Environment , 2013, IEEE Transactions on Intelligent Transportation Systems.

[38]  Tingru Zhang,et al.  The association between driving anger and driving outcomes: A meta-analysis of evidence from the past twenty years. , 2016, Accident; analysis and prevention.

[39]  N. Jewell,et al.  To GEE or Not to GEE: Comparing Population Average and Mixed Models for Estimating the Associations Between Neighborhood Risk Factors and Health , 2010, Epidemiology.

[40]  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 .

[41]  T. Dingus,et al.  Distracted driving and risk of road crashes among novice and experienced drivers. , 2014, The New England journal of medicine.

[42]  Siegfried Rothe,et al.  Can talking on the phone keep the driver awake?: results of a field-study using telephoning as a countermeasure against fatigue while driving , 2011 .

[43]  Josef F. Krems,et al.  Using an infotainment system while driving: a continuous analysis of behavior adaptations , 2013 .

[44]  J.C.F. de Winter,et al.  The Driver Behaviour Questionnaire as a predictor of accidents: a meta-analysis. , 2010, Journal of safety research.

[45]  K. Govender,et al.  The influence of anger, impulsivity, sensation seeking and driver attitudes on risky driving behaviour among post-graduate university students in Durban, South Africa. , 2013, Accident; analysis and prevention.

[46]  J. Conger,et al.  A quantitative review of the relationship between anger and aggressive driving , 2007 .

[47]  Jeff K Caird,et al.  Safety-critical event risk associated with cell phone tasks as measured in naturalistic driving studies: A systematic review and meta-analysis. , 2016, Accident; analysis and prevention.

[48]  Richard Young,et al.  Revised Odds Ratio Estimates of Secondary Tasks: A Re-Analysis of the 100-Car Naturalistic Driving Study Data , 2015 .

[49]  Mark Vollrath,et al.  How the presence of passengers influences the risk of a collision with another vehicle. , 2002, Accident; analysis and prevention.

[50]  E. Dahlen,et al.  The Big Five factors, sensation seeking, and driving anger in the prediction of unsafe driving☆ , 2006 .

[51]  M. Zuckerman Behavioral Expressions and Biosocial Bases of Sensation Seeking , 1994 .

[52]  Marco Dozza,et al.  Driving context influences drivers' decision to engage in visual-manual phone tasks: Evidence from a naturalistic driving study. , 2015, Journal of safety research.

[53]  Bryan Reimer,et al.  Self-reported and observed risky driving behaviors among frequent and infrequent cell phone users. , 2013, Accident; analysis and prevention.

[54]  C. F. Bond,et al.  Social facilitation: a meta-analysis of 241 studies. , 1983, Psychological bulletin.

[55]  Julie Hatfield,et al.  The role of risk-propensity in the risky driving of younger drivers. , 2009, Accident; analysis and prevention.

[56]  Per Ole Wanvik,et al.  A new method for assessing the risk of accident associated with darkness. , 2009, Accident; analysis and prevention.

[58]  Richard Rowe,et al.  Measuring errors and violations on the road: a bifactor modeling approach to the Driver Behavior Questionnaire. , 2015, Accident; analysis and prevention.

[59]  Michael Sivak,et al.  Differentiation of Visibility and Alcohol as Contributors to Twilight Road Fatalities , 1996, Hum. Factors.

[60]  Mollie E. Brooks,et al.  Generalized linear mixed models: a practical guide for ecology and evolution. , 2009, Trends in ecology & evolution.

[61]  Tingru Zhang,et al.  Dimensions of driving anger and their relationships with aberrant driving. , 2015, Accident; analysis and prevention.

[62]  D. Strayer,et al.  Cell phone-induced failures of visual attention during simulated driving. , 2003, Journal of experimental psychology. Applied.

[63]  J. Groeger,et al.  Drivers Display Anger-Congruent Attention to Potential Traffic Hazards , 2013 .

[64]  Dennis R Durbin,et al.  Special considerations in distracted driving with teens. , 2014, Annals of advances in automotive medicine. Association for the Advancement of Automotive Medicine. Annual Scientific Conference.

[65]  David L. Strayer,et al.  Measuring Cognitive Distraction in the Automobile , 2013 .

[66]  Patricia Delhomme,et al.  Personality predictors of speeding in young drivers: Anger vs. sensation seeking , 2012 .

[67]  Pei-Sung Lin,et al.  Naturalistic Driving Study: Field Data Collection , 2014 .