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This study updates previous IIHS studies comparing estimated delta Vs for crash tested vehicles to the distribution of estimated delta Vs in the National Automotive Sampling System (NASS) Crashworthiness Data System (CDS). The delta V estimates for 232 frontal crash tests at 64.4km/h into a deformable barrier with 40 percent overlap are compared with estimates from frontal offset crashes in the 1997-2004 NASS database. All delta V estimates were based on SMASH, the delta V estimating program used by NASS since 1997. Results indicated that for all vehicles tested by IIHS, SMASH delta Vs were, on average, 32 percent lower than impact speeds and about 28 percent lower than the expected delta V. Almost 80 percent of all real-world frontal crashes resulting in AIS 3+ injuries and just over 60 percent of all fatal crashes occur at or below the average estimated delta V calculated for crash tested vehicles.
Cyclists are more likely to be injured in fatal crashes than motorised vehicles. To gain detailed and precise behavioural data of road users, i.e. trajectories, a measuring campaign was conducted. Therefore, a black-spot for accidents with cyclists in Berlin, Germany was selected. The traffic has been detected by a fully automated traffic video analysis system continuously for twelve hours. The video surveillance system is capable of automatically extracting trajectories, classifying road user types and precise determining and positioning of conflicts and accidents. Additionally, pre-conflict and pre-accident situations could be analysed to provide further in-depth understanding of accident causation. The evaluation of the measuring campaign comprised the investigation of traffic parameters, e.g. traffic flow, as well as traffic-safety related parameters based on Surrogate Safety Measures (SSM). Furthermore, the spatial and temporal distributions of conflicts involving cyclists were determined. As a result, three possible conflict clusters could be identified, of which one cluster could be confirmed by detailed video analysis, showing conflicts caused by right turning vehicles.
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.
The share of high-tensile steel in car bodies has increased over the last years. While occupant safety has generally benefited from this measure, there is a potential risk that, as a result, rescue time may increase considerably. In more than 60% of all car occupant fatalities a technical rescue has been necessary. These are in particular those cases where occupants die immediately at the accident scene. Therefore, in these cases "rescue time" is a very sensitive parameter. In addition to the general analysis of the need of technical rescue and the actual rescue time depending on model years, the injury pattern of occupants requiring technical rescue will be analysed to provide advice for rescue teams. Furthermore, a detailed analysis of rescue measures for the most popular car models depending on the safety cell design is given.
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 number of injuries sustained by car occupants involving the head, thorax, spine, pelvis and the upper limbs have been reduced significantly during recent years. This is probably due to better safety features in the cars, especially the availability and usage of safety belts, airbags etc. Therefore one can notice clinically a relative increase in survivors of severe frontal crashes, but many of them have injuries to the lower extremities. To verify this, we analyzed the foot and ankle injuries of front seat passengers.
The purpose of this work is to investigate the association between the injuries in motorcycle accident and the main accident configurations. The data were provided by a multicentric case-control study MAIDS regarding the risk of crash and injuries of motorcyclists. Chi-square test was used to evaluate the relationship between the variables and a logistic regression was performed to evaluate the association of injury severity with some variables supposed to be predictive factors. Lesive patterns characterized by internal haemorrhages are mainly associated with fronto-lateral crashes, above all in urban areas. Lacerations or abrasions, mainly reported in torso and lower extremities, are mostly associated with single crashes or accidents in queue also for crashes occurred to low speed (< 50 km/h). The severity of injuries is highly associated with impact speed, regardless of the crash configuration. Fractures and haemorrhages play an important role in determining the severity of injuries. The upper extremities are the most frequently traumatised anatomic areas.
Novice drivers are at high risk for crash involvement. We performed an analysis of causations, injury patterns and distributions of novice drivers in cars and on motorcycles in road traffic as a basis for proper measurements. Method Data of accident and hospital records of novice drivers (licence < 2 years) were analysed focusing the following parameters: injury type, localisation and mechanism, Abbreviated Injury Scale (AIS), maximum AIS (MAIS), delta-v, collision speed and other technical parameters and have been compared to those of experienced drivers. In 18352 accidents in the area of Hannover (years1985"2004), 2602 novice drivers and 18214 experienced drivers were recorded having an accident. Novice car drivers were more often and severe injured than experienced and on motorcycles the experienced riders were at higher risk. Novice drivers of both groups sustained more often extremity injuries. 4.5 % novice car drivers were not restraint compared to 3.7 % of the experienced drivers and 6.1 % novice motorcycle drivers did not wear a proper helmet (versus 6.5 %). Severe injuries sustained at a rate of 20 % at collision speeds below 30 km/h and in 80% at collision speeds above 50 km/h. Novice car drivers drove significant older cars. The risk profile of novice drivers is similar to those of drivers older than 65 years. Structural protection and special lectures like skidding courses could be proper remedial action next to harder punishment of violations.
A lot of factors are related to a road traffic accident; particularly human factors such as road use characteristic, driving maneuver characteristic and safety attitude are the major ones. As a random factor is also included, so it is necessary to minimize the contribution of a random factor to identify human factors related to a road traffic accident. There are several standpoints for traffic accident analysis, such as vehicle-based, location-based and driver-based. And it is effective to analyze driver-based traffic accident data for discussion on the relation between human factors and accidents. An integrated traffic accident database system was developed for analysis considering driver- accident and violation records by ITARD, and several studies were carried out for the evaluation. Useful data for discussion on the relation between types of collision and traffic violations, and the effect of accident experience to the following accident were obtained.
Intelligente Bauwerke - Anforderungen an die Aufbereitung von Messgrößen und ihrer Darstellungsform
(2015)
Ziel des Forschungsvorhabens FE 15.0548/2011/GRB war die Ausarbeitung einer Konzeption zu Anforderungen an die Aufbereitung und Verarbeitung von Messgrößen und ihrer Darstellung. Dies beinhaltete die Evaluierung und Entwicklung verschiedener modellbasierter und statistischer Analyseverfahren, die über den bisherigen Stand der Technik der Bauwerksüberwachung hinausgehen. Der Nutzen liegt in der Herausfilterung relevanter Informationen aus umfangreichem Datenmaterial (Vor-Aggregation) sowie der Erzeugung von belastbaren Zustandsinformationen bzw. Vorergebnissen hierzu durch eine frühzeitige, leistungsfähige Plausibilisierung. Es wurde gezeigt, dass durch den Einsatz von leistungsfähigen, gedächtnisbehafteten, selbstlernenden Algorithmen für die Sensorfusion, Interpolation, Plausibilitätserhöhung und Treffen fachtechnischer Monitoringaussagen Ergebnisse erzielt werden können, die bezüglich der Verarbeitung von Mess- und Erfassungsdaten weit über den aktuellen Stand beim Brückenmonitoring hinausgehen. Anhand mehrerer Szenarien, für die reale Erfassungsdaten zur Verfügung standen, wurde gezeigt, dass diese Verfahren sehr zuverlässig verschiedenste Signalstörungen, wie Messausreisser, erhöhtes Rauschen und Brummeinstreuung erkennen können. Nur durch die frühzeitige und zuverlässige Plausibilisierung von Sensordaten von Brückenbauwerken kann verhindert werden, dass offensichtlich fehlerhafte Messwerte (wie z.B. Messausreisser, störungsbehaftete Messungen) zu falschen Vorhersagen der Systemzuverlässigkeit von Brückenbauwerken durch rechnergestützte Systemmodelle führen.