Causation patterns and data collection blind spots for fatal intersection accidents in Norway
Övrigt konferensbidrag, 2010
Norwegian fatal intersection accidents from the years 2005-2007 were analysed to identify any causation patterns
among their underlying contributing factors, and also to evaluate whether the data collection and documentation procedures
used by the Norwegian in-depth investigation teams produces the information necessary to perform causation pattern
analysis. A total of 28 fatal accidents were analysed. Details on crash contributing factors for each driver in each crash were
first coded using the Driving Reliability and Error Analysis Method (DREAM), and then aggregated based on whether the
driver was going straight or turning. Analysis results indicate that turning drivers to a large extent are faced with perception
difficulties and unexpected behaviour from the primary conflict vehicle, while at the same time trying to negotiate a
demanding traffic situation. Drivers going straight on the other hand have less perception difficulties. Instead, their main
problem is that they largely expect turning drivers to yield. When this assumption is violated, they are either slow to react or
do not react at all. Contributing factors often pointed to in literature, e.g. high speed, drugs and/or alcohol and inadequate
driver training, played a role in 12 of 28 accidents. While this confirms their prevalence, it also indicates that most drivers
end up in these situations due to combinations of less auspicious contributing factors.
In terms of data collection and documentation, information on blunt end factors (those more distant in time/space, yet
important for the development of events) was more limited than information on sharp end factors (those close in time/space
to the crash). A possible explanation is that analysts may view some blunt end factors as event circumstances rather than
contributing factors in themselves, and therefore do not report them. There was also an asymmetry in terms of reported
obstructions to view due to signposts and vegetation. While frequently reported as contributing for turning drivers, they were
rarely reported as contributing for their counterparts in the same accidents. This probably reflects an involuntary focus of the
analyst on identifying contributing factors for the driver legally held liable, while less attention is paid to the driver judged
not at fault. Since who to blame often is irrelevant from a countermeasure development point of view, this underlying
investigator mindset needs addressing to avoid future bias in crash investigation reports.
Driver behaviour analysis
In-depth data collection
Accident causation