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The role of a national motor vehicle crash causation study-style data set in rollover data analysis
(2010)
On 1 January 2005, The National Highway Traffic Safety Administration, an agency of the United States Department of Transportation, implemented a new data collection strategy designed to assess crash avoidance technologies and report associated behavioral inputs and outcomes. The original goal was a six-year program, however, during the shortened data collection period; it proved a valuable resource for understanding a precrash environment previously obscured by forensic case investigation. Another unintended consequence was an overlap with infrastructure, roadway geometry, and design with the occupant and vehicle outcomes, by virtue of well-defined attributes. External to the collected data, supplementary information was extrapolated, by using manuals published in the United States, by the American Association of State Highway Transportation Officials and selected State Departments of Transportation, in conjunction with the National Motor Vehicle Crash Causation Study (NMVCCS). This provided a backdrop to the infrastructure framework of the rollover problem within which the occupant and vehicle outcomes were studied. If a NMVCCS-style data collection were to be implemented elsewhere, then complementary manuals produced by federal transportation officials might be consulted producing similar relationships. The current study uses NMVCCS data to describe vehicles travelling through diverse design geometries and the outcome for occupants involved in crashes within that system. Codified and extrapolated data form the basis for assessing NMVCCS and its value to the transportation safety community, as the protocols are applicable universally. The benefit in continuing a NMVCCS-style study is noted, as the interaction of roadway infrastructure and occupant protection agencies might find paths to better work together in solving the complex rollover problem using a common data-driven approach.
The NHTSA-sponsored Crash Injury Research and Engineering Network (CIREN) has collected and analyzed crash, vehicle damage, and detailed injury data from over 4000 case occupants who were patients admitted to Level-I trauma centers following involvement in motor vehicle crashes. Since 2005, CIREN has used a methodology known as "BioTab" to analyze and document the causes of injuries resulting from passenger vehicle crashes. BioTab was developed to provide a complete evidenced-based method to describe and document injury causation from in-depth crash investigations with confidence levels assigned to the causes of injury based on the available evidence. This paper describes how the BioTab method is being used in CIREN to leverage the data collected from in-depth crash investigations, and particularly the detailed injury data available in CIREN, to develop evidence-based assessments of injury causation. CIREN case examples are provided to demonstrate the ability of the BioTab method to improve real-world crash/injury data assessment.
Unfortunately, there has been a high number of accident fatalities reported in the Czech Republic in recent years. There are many causes which have led to a growth in the number of road traffic accidents. Since 1990, traffic density has demonstrated an upward moving tendency, daily traffic-jams are on the increase in many cities and traffic capacity on roads and streets is not able to satisfy this increasing density. Moreover, many road users lack experience in terms of driving modern cars. The National Accident Study of the Czech Republic is based on the assumption that the year 2010 is considered as a pilot project with the testing operation of collecting and evaluating data from traffic accidents. From the beginning of 2011, a fully-functional structure of the Traffic Accident Research will be created and solid data generated. Based on this assumption, we hope to begin meaningful cooperation with foreign countries.
A national initiative from the vehicle manufacturers, safety system suppliers, the road administration and universities in Sweden took off in 2007. The aim was to develop a national investigation network and a methodology focusing on all phases of a crash (pre-crash, in-crash and post-crash) as well as all parts of the road transport system (road user, vehicle and road environment). The initiative is formally run as a project with the acronym INTACT (Investigation Network and Accident Collection Techniques). It was a three year pilot with the aim to develop methodologies for an extended national crash investigation activity. During the first year the INTACT partners agreed on the aim for the investigation and methods for retrieving the data were developed. During the second and third year the methodology was tested in real-world investigations and further refinement was made. The paper describes the methodology developed to obtain high qualitative in-depth road crash data.
In India, heavy truck crashes on national highways account for a number of fatalities. But due to lack of in-depth crash data, detailed analysis is not possible to determine injury mechanisms, and to identify infrastructure, vehicle and human factors affecting these crashes. Over the past two years, researchers in India have established a crash investigation network, with the co-operation of the police and hospitals, to conduct crash investigations and in-depth crash data collection on national highways in the state of Tamil Nadu. This pioneering effort has resulted in the development of a heavy truck crash investigation methodology, the outcome of which is scientific and reliable crash data that has been able to provide good insight into truck crashes and their causes. This paper explains the need for truck crash investigations, the methodology, conclusions of the data analyzed up to date, and the need to focus on truck driver working conditions.
Causation patterns and data collection blind spots for fatal intersection accidents in Norway
(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.
Accidents with vulnerable road users require special attention within the road safety work because these accidents are often accompanied with severe injuries. Thus In 2006 at least 6200 Powered Two Wheeler (PTW) riders were killed in road crashes in the EU 25 representing 16% of the total number of road deaths while accounting for only 2% of the total kilometers driven. For the prevention of accidents with VRU above all the knowledge of the causes of the accidents is of special importance. This study is based on the methodology of the German In-Depth Accident Study GIDAS. Within GIDAS extensive data on various fields of accidentology are collected on-scene from road traffic accidents with injuries in the Hannover and Dresden area. Using a well defined sample plan the collected data is highly representative to the whole German situation (Brühning et al, Otte et al). The need of in-depth accident causation data in accident research led to the development of a special tool for the collection of such data called ACASS (Accident Causation Analysis with Seven Steps), which was implemented in the GIDAS methodology in 2008 and described by Otte in 2009.