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Nowadays, traffic accidents are recorded in historical databases. Regarding the huge quantity of data, the use of data mining tools is essential to help Experts, for automatically extracting relevant information in order to establish and quantify relations between severity and potential factors of accidents. An innovative approach is here proposed for an in depth investigation of real world accidents data base. Mutual information ratio based on conditional entropies is used to quantity the association strength between an accident outcome descriptor (injury severity) and other potential association factors. Information theoretic methods help to select automatically groups of factors mostly responsible of the severity of accident.
The increase in light duty trucks (LDT) on the road in the US is a safety concern because of their aggressivity, or risk they present to occupants of cars, especially in side impacts. We use FARS data to look at fatality trends in frontal and side impacts between cars and LDT. FARS data is also used to determine risk, or fatalities per registered vehicle, imposed on car drivers from other vehicle types. We use NASS CDS data to investigate sources of serious injuries in vehicles with side impact. These sources of injury are categorized into three major groups: 1) contact without intrusion, 2) contact with intrusion, and 3) restraints. We find a greater fraction of intrusion related injuries in cars struck on their side by SUV or pick-up trucks than when they are struck by other cars.
In Finland all fatal motor vehicle accidents are studied in-depth on-the-spot by multidisciplinary (police, road and vehicle engineers, physician and behavioural scientist) road accident investigation teams (legislation 2001, work started 1968), which operate in every province. The purpose of the teams is to uncover risk factors that turned an ordinary driving situation into a serious accident and give safety recommendations for improving road safety. The investigation teams do not take a stand on guilt or insurance compensation. When analysing accidents the teams use the concepts of key event, immediate, background and injury risk factors. Compiled investigation folders of each case contain investigation forms from each member, preinvestigation protocol, photographs, sketches etc. About 500 items of information are collected from each accident party. The collected information is also coded into a computer database. Both the database and the investigation folders are widely utilized by researchers and authorities conducting safety work.
Females sustain Cervical Spine Distortion injury (CSD) more often than males. Most work dealing with the biomechanics background (e.g. injury mechanism/criteria) as well as the application in seat design/testing, focuses on the occupant model of an average male. Therefore the EU-Project ADSEAT (Adaptive Seat to Reduce Neck Injuries for Female and Male Occupants) is aimed at adding a female model for gender balanced research of CSD and improving seat design. An extensive literature review, searching for risk factors and injury criteria for males and females, was accompanied by the evaluation of different databases containing CSD cases. The database evaluations suggests that an anthropometry quite close to the 50%ile female anthropometry as known from crash test dummy design is appropriate. The results presented here form the basis for the future development of a computational female model and the improvement of seat design for better protection of both males and females in the frame of the ADSEAT-Project.
Relevant accident related factors : risk and frequencies of contributing to road traffic accidents
(2009)
In the course of the European Project TRACE (Traffic Accident Causation in Europe) an attempt was made to analyse the cause of road traffic accidents from a factors' point of view. By literature review the most important independent risk factors for traffic accidents were identified to be speed, alcohol intake, male gender, young age, cell phone use, and fatigue. However, the impact of an accident related factor also depends on its prevalence in traffic and accidents, respectively. Available to the Partners in the TRACE Project were different accident databases. Causally contributing factors found by accident investigations that are most often coded in accident databases are connected to unadapted speed and inattention. Taking into account the risk increase and the frequency of contribution to accidents the conclusion can be drawn that the most relevant factors for accident causation are: "alcohol", "speed", and "inattention and distraction".