The role of driver distraction in traffic crashes

By J. Stutts, D. Reinfurt, L. Staplin, E. Rodgman. 2001

563 citations recorded by the source corpus.

Subfields: Safety, Risk, Reliability and Quality, Social Psychology

View Paper: https://www.semanticscholar.org/paper/1693da1312967628a8ddf0bb2bfb88e69ddbb840

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In Safety, Risk, Reliability and Quality

In Social Psychology

Citations in the corpus

Driver Inattention Monitoring System for Intelligent Vehicles: A Review (2009, background): “The causes of driver distraction are diverse and pose large risk factors—more than half of the crashes that involve inattention were caused by driver distraction [1], [2].”
Vehicle Detection Techniques for Collision Avoidance Systems: A Review (2015, background): “kinds of possibly distracting activities are [7]: drinking or eating, outdoor people, event or object, talking or listening”
Driver distraction : a review of the literature (2007, unknown): “Stutts et al. (2001) conducted a study for the AAAFTS in which they examined detailed crash records from the Crashworthiness Data System (CDS) collected between 1995 and 1999.”
Generation of landmark-based navigation instructions from open-source data (2012, background): “Minimizing driver distraction is a crucial goal of improved navigation systems, as driver inattention of various kinds is a leading cause of traffic accidents (25% of all policereported car crashes in the US in 2000, according to Stutts et al. (2001)).”
DISTRACTIONS IN EVERYDAY DRIVING (2003, methodology): “Summary of Study Findings .............................61 Limitations ......................................................63 Significance and Implications for Reducing Crashes ......................................65 REFERENCES • 67 APPENDIX A PART A • 69 Design Specifications for In-Vehicle Instr”
Driver distraction: A review of the literature (2003, unknown): “However, as more wireless communication, entertainment and driver assistance systems proliferate the vehicle market, it is probable that the rate of distraction-related crashes will escalate (Stutts et al., 2001).”
Real-Time Detection of Driver Cognitive Distraction Using Support Vector Machines (2007, background): “driver distraction, resulting in as many as 5000 fatalities and $40 billion in damages each year [1]–[3].”