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Exploring inattention and distraction in the SafetyNet Accident Causation Database
journal contributionposted on 03.05.2013, 12:40 by Rachel TalbotRachel Talbot, Helen Fagerlind, Andrew MorrisAndrew Morris
Distraction and inattention are considered to be very important and prevalent factors in the causation of road accidents. There have been many recent research studies which have attempted to understand the circumstances under which a driver becomes distracted or inattentive and how distraction/inattention can be prevented. Both factors are thought to have become more important in recent times partly due to the evolution of in-vehicle information and communication technology. This study describes a methodology that was developed to understand when factors such as distraction and inattention may have been contributors to crashes and also describes some of the consequences of distraction and inattention in terms of subsequent driver actions. The study uses data relating to distraction and inattention from the SafetyNet Accident Causation Database. This database was formulated as part of the SafetyNet project to address the lack of representative in-depth accident causation data within the European Union. Data were collected in 6 European countries using ‘on-scene’ and ‘nearly on-scene’ crash investigation methodologies. 32% of crashes recorded in the database, involved at least one driver, rider or pedestrian, who was determined to be ‘Inattentive’ or ‘Distracted’. 212 of the drivers were assigned ‘Distraction’ and 140 drivers were given the code ‘Inattention’. It was found that both distraction and inattention often lead to missed observations within the driving task and consequently ‘Timing’ or ‘Direction’ become critical events in the aetiology of crashes. In addition, the crash types and outcomes may differ according to the type and nature of the distraction and inattention as determined by the in-depth investigations. The development of accident coding methodology is described in this study as is its evolution into the Driver Reliability and Error Analysis Model (DREAM) version 3.0.