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Who doesn't wear seat belts?
(2009)
Using real world accident data, seat belts were estimated to be 61% effective at preventing fatalities, and 32% effective at preventing serious injuries. They were most effective for drivers with an airbag. Seat belts were estimated as having prevented 57,000 fatalities and 213,000 seriously injured casualties in the UK since 1983. Seat belt legislation was estimated to have prevented 31,000 fatalities and 118,000 seriously injured casualties. A future increase in effective seat belt wearing rate (which takes into account seating position) in the UK from 92.5% to 93% may prevent casualties valued at a societal cost of over -£18 million per year. To target a seat belt campaign, the question "who doesn"t wear seat belts?" must be answered. Seat belt wearing rates and the number of unbelted casualties were analysed. It was primarily young adult males who didn"t wear seat belts, and they made up the majority of unbelted fatalities and seriously injured casualties.
Impact severity is a fundamental measure for all in-depth crash investigation projects. One methodology used in the UK is based on the US Calspan software package CRASH3. The UK- in-depth crash investigation studies routinely use AiDamage3 a software package which is based on an updated version of the original CRASH3 algorithm, including enhancements to the vehicle stiffness coefficients. Real world accident-damaged vehicles are measured and their crush is correlated with a library of stiffness coefficients. These measurements are then used, along with other parameters, to calculate the crash energy and equivalent changes of velocity of the vehicles (delta-v), which is a measure of the impact severity. UK in-depth accident studies routinely validate the crash severity methodologies applied as the vehicle fleet changes. This is achieved by analysing crash test data and using the appropriate residual crush damage and other inputs to AiDamage3 and checking the program- outputs with the known crash severity parameters. This procedure checks, at least in part, the default stiffness values in the data libraries and the reconstruction methods used.
The aim of this study was to evaluate the performance and accuracy of Event Data Recorders (EDRs). The analysis was based on J-NCAP crash tests from 2006"2007, with the corresponding EDR datasets. The pre-crash velocity, maximum delta-V and delta-V versus time history data recorded in the EDRs were compared with the reliable crash test data. The difference between the EDR pre-crash velocity and the laboratory test speed was less than 4 percent. In contrast, in several cases the maximum delta-V and delta-V versus time history data obtained from the EDRs showed uncertainty of measurement in comparisons with the reliable delta-V data. The difference in maximum delta-V in these comparisons was more than 5 percent in 10 of 14 tests and more than 10 percent in 4 of 14 tests. The EDRs underestimated the maximum delta-V in almost all tests. It was also concluded that the calculated acceleration from the EDR delta-V versus time history data showed good agreement with the instrumented accelerometer signal during the collision in almost all tests.
The bicyclist accidents were analyzed to get better understanding of the occurrences and frequency of the accidents, injury distributions, as well as correlation of injury severity/outcomes with engineering and human factors in two different countries of China and Germany. The accident cases that occurred from 2001 to 2006 were collected from IVAC database in Changsha and GIDAS database in Hannover. Based on specified sampling criteria, 1,570 bicyclist cases were selected from IVAC database in Changsha, and 1806 cases were collected from Hannover, documented in GIDAS database. Statistical analyses were carried out by using these selected data. The results from the statistical analysis are presented and discussed in this study.
This study aims to analyze spine injuries in motor vehicle accidents. Between 1985 and 2004 the Hannover accident research unit documented 18353 accidents. We identified 161 front passengers (0.53%) with cervical spine injuries, 84 (0.28%) with thoracic and 95 (0.31%) with lumbar injuries. Technical and medical data was reviewed. Patients" records were retrieved. X-rays were evaluated and fractures were classified according to the Magerl classification. 68% and 57% of thoracic and lumbar fractures occurred in accidents with multiple impacts. Delta-v was 50, 40 and 40 kph in passengers with cervical, thoracic and lumbar spine, resp. Passengers with spinal fractures frequently showed numerous concomitant injuries, e.g. additional vertebral fractures. The influence of seat belts and airbags is discussed. Patient work-up has to include a thorough investigation for additional injuries.
In a first step, we have examined approximately 23 000 single vehicle accidents within the Austrian National Statistics database. In a second step, we considered 15% of all fatal "running off the road" accidents that occurred in Austria in 2003. As a result, two accident categories were specified; "leaving the road without preceding manoeuvre" and "leaving the road with preceding manoeuvre". These two categories can be basically characterised by the vehicle- heading angle and its velocity angle. In this report, we further suggest theoretical approaches for the dimensioning of a safety zone, an area adjacent to the road free of fixed objects or dangerous slopes. We also show the link between the two accident categories mentioned above and the real world accidents analysed in detail. These observations also form the basis for the required length for safety devices. Finally, we summarise accident avoidance strategies.
The focus of the technical innovation in the automobile industry is currently changing to sensor based safety systems, which are operating in the pre-crash phase of an accident. To get more information about this pre-crash phase for real accidents a simulation of this phase using the GIDAS database is done. The basics for this simulation are geometrical information about the accident location and the exact accident data out of the GIDAS database. This aggregated information gives the possibility to simulate an exact motion for every accident participant, using MATLAB / SIMULINK, in the pre-crash phase. After the simulation the information about the geometrical positions, the velocities and maneuvers of the drivers to an individual TTC (time to collision) are available. With those results it is possible to develop new useful sensor geometries using pre-crash scatter plots or estimate the efficiency of implemented active safety systems in combination with sensor characteristics. This simulation can be done for every reconstructed accident included in the GIDAS database, so these results can represent a wide spread basis for the further development of active safety systems and sensor geometries and characteristics
In Germany averagely two million traffic accidents happen each year and emergency medical services are called to more than 400 000 patients. Even though this number is decreasing continuously (due to improvements in the fields of vehicle safety, road construction, and accident prevention) every case is yet a challenge for the rescuers and requires improvements in emergency medicine as well. Especially during diagnostics right at the accident scene, there are only limited instruments available to gain the necessary knowledge of the injuries suffered, to come to essential decisions about treatment or transport. To provide an additional diagnostic aid by scouting and estimating the situation, a software-tool calculating the likeliness of the most frequent severe injuries (AIS 3-6) of front occupants in passenger cars has been developed to deliver this necessary information about particular accident scenarios. To achieve this, logistic likelihood functions have been calculated in a multivariate regression analysis analysing all AIS 3+ injuries in the GIDAS database of the years 1999-2006 that happened more than four times
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".
A set of recommendations for pan-European transparent and independent road accident investigations has been developed by the SafetyNet project. The aim of these recommendations is to pave the way for future EU scale accident investigation activities by setting out the necessary steps for establishing safety oriented road accident investigations in Member States. This can be seen as the start of the process for establishing road accident investigations throughout Europe which operate according to a common methodology. The recommendations propose a European Safety Oriented Road Accident Investigation Programme which sets out the procedures that need to be put in place to investigate a sample of every day road accidents. They address four sets of issues; institutional addressing the characteristics of the programme; operational describing the conditions under which data isrncollected; data storage and protection; and reports, countermeasures and the dissemination of data.rn