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What can the drivers’ own description from combined sources provide in an analysis of driver distraction and low vigilance in accident situations?

Accident Analysis & Prevention
Publication Date
DOI: 10.1016/j.aap.2012.12.016
  • Case Study
  • Driver Distraction
  • Low Vigilance
  • Drowsiness
  • Mail Survey Questionnaire
  • Insurance Claims


Abstract Accident data play an important role in vehicle safety development. Accident data sources are generally limited in terms of how much information is provided on driver states and behaviour prior to an accident. However, the precise limitations vary between databases, due to differences in analysis focus and data collection procedures between organisations. If information about a specific accident can be retrieved from more than one data source it should be possible to combine the available information sets to facilitate data from one source to compensate for limitations in the other(s). To investigate the viability of such compensation, this study identified a set of accidents recorded in two different data sources. The first data source investigated was an accident mail survey and the second data source insurance claims documents consisting predominantly of insurance claims completed by the involved road users. An analysis of survey variables was compared to a case analysis including word data derived from the same survey and filed insurance claims documents. For each accident, the added value of having access to more than one source of information was assessed. To limit the scope of this study, three particular topics were investigated: available information on low vigilance (e.g., being drowsy, ill); secondary task distraction (e.g., talking with passengers, mobile phone use); and distraction related to the driving task (e.g., looking for approaching vehicles). Results suggest that for low vigilance and secondary task distraction, a combination of the mail survey and insurance claims documents provide more reliable and detailed pre-crash information than survey variables alone. However, driving related distraction appears to be more difficult to capture. In order to gain a better understanding of the above issues and how frequently they occur in accidents, the data sources and analysis methods suggested here may be combined with other investigation methods such as in-depth accident investigations and pre-crash data recordings.

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