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Bus or heavy vehicle passenger accidents are rare events, compared with car accidents, but sometimes leads to a large number of victims especially in rollover crash scenarios. Two accidents occurred in Portugal in 2007 and 2013 in which 28 people died and more than 50 are injured, shown the importance of the investigation of such accidents. For the investigation of these accidents multidisciplinary teams are constituted with engineers and police officers. All the factors involved are taken into consideration including road design, traffic signs, maintenance and hardware, human factors, and vehicle factors. In this work a methodology to an accurate collection of the data is proposed. From the information collected the accident is reconstructed using the PC-CrashTM software. From this all the contribution factors are determined and recommendations to mitigate these crashes are listed. These two accidents are rollover accidents and the analysis of the injuries and its correlation with the use of retention systems is very important. From the medical data and with the dynamics of the accident determined simulations of the occupants with biomechanical models are carried out in order to evaluate the effect of the retention systems in the injuries. This analysis is based on injury criteria (such as Abbreviated Injury Score (AIS) or Injury Severity Scale (ISS)). With this it is possible to determine if the seat belt was worn or not.
Since its creation in 2011 the Pre-Crash-Matrix (PCM) offers the possibility to observe the pre-crash phase until five seconds before crash for a wide range of accidents. Currently the PCM contains more than 8.000 reconstructed accidents out of the GIDAS (German In-Depth Accident Study) database and is enlarged continuously by more than 1.000 cases per year. Hence, a detailed investigation of active safety systems in real accident situations has been made feasible. The PCM contains all relevant data in database format to simulate the pre-crash phase until the first collision of the accident for a maximum of two participants. This includes the definition of the participants and their characteristics, the dynamic behavior of the participants as time-dependent course for five seconds before crash as well as the geometry of the traffic infrastructure. The digital sketch of the accident and information from GIDAS as well as from supplementary databases represent the main input for the simulation of the pre-crash phase of an accident with the VUFO simulation model VAST (Vufo Accident Simulation Tool). This simulation in turn embodies the foundation of the PCM. The PCM underlies continual improvements and enhancements in consultation with its users. In addition to collisions of cars with other cars, pedestrians, bicycles and motorcycles the PCM now also covers car to object and car to truck collisions. The paper illustrates car to truck collisions as a showcase and explains perspectives for further developments. In 2016 a more detailed definition of the contour of the vehicle was added. Furthermore, the geometrical surroundings of the accident site will be provided in a new structure with a higher level of detail. Thus, a precise classification of road marks and objects is possible to further improve the support of developing and evaluating ADAS. This paper gives an overview about the latest developments of the PCM with its innovations and provides an outlook to upcoming enhancements. Besides potential areas of application for the development of ADAS are shown.
Causation of traffic accidents with children from the perspective of all involved participants
(2017)
In the year 2014 about 2,800 children between zero and 14 years got injured due to traffic accidents in Austria. More than 50% were taking part in traffic as active road users like cyclists or pedestrians. Within this study 46 real world traffic accidents between vehicles and children as pedestrians were analysed. In 39 cases, car drivers hit the crossing children. In the other cases, the collision opponents were busses, trucks or motorcycles. Most of the children got hit while crossing a road at urban sites. By analysing the traffic accidents from the perspectives of all involved participants, vehicle drivers and injured children, it is possible to identify factors for each participant, which led to the accident and factors that contributed the accident. The main task is to find patterns in the behaviour of crash victims (children and driver) before the collision. One important fact is that in more than 50% of the analysed cases sight obstructions were an important contributing factor for both, the driver and the child. From drivers view situations in which the child moved unexpected into the driven road lane were often found. For the injured child, factors like: no attention to the road traffic or no sufficient traffic observation were found to be relevant. Further it- possible to sensitise children and adults to possible source of critical traffic situations according to the findings of this study.
For more than a decade, ADAC accident researchers have analysed road accidents with severe injuries, recording some 20,000 accidents. An important task in accident research is to determine the causative factors of road accidents. Apart from vehicle engineering and human factors, accident research also focuses on infrastructural and environmental aspects. To find out what accident scenarios are the most common in ADAC accident research and what driver assistance systems can prevent them, our first task was to conduct a detailed accident analysis. Using CarMaker, we performed a realistic simulation of accident scenarios, including crashes, with varying parameters. To begin with, we made an initial selection of driver assistance systems in order to determine those with the greatest accident prevention potential. One important finding of this study is that the safety potential of the individual driver assistance systems can actually be examined. It also turned out that active safety offers even much more potential for development and innovation than passive safety. At the same time, testing becomes more demanding, too, as new systems keep entering the market, many of them differing in functional details. ADAC will continue to test all driver assistance systems as realistically as possible so as to be able to provide advice to car buyers. Therefore, it will be essential to develop and improve test conditions and criteria.
Powered Two Wheeler (Motorcycle) crashes are overrepresented in EU, England, and United States casualty statistics for both fatal and serious injuries. While regional geographic differences are evident for motorcycle size, type, and engine displacement, the casualty statistics consistently indicate significantly higher injury rates for all motorcycle riders when compared to car occupants. Accident analysis and reconstruction of these motorcycle crashes is a necessary process to gain further understanding of potential injury mitigation strategies. This paper focuses on the analysis of the rider post impact trajectory in the immediate moments following a crash. The rider and motorcycle, while loosely coupled by seating position leading up to a crash, quickly decouple as the crash forces develop. As a result, the rider moves relative to the motorcycle and relative to the collision partner. This movement, or trajectory, is primarily influenced by the type and configuration of the impact, the type and configuration of the motorcycle and collision partner, and the speeds involved. Understanding the rider's post impact trajectory will assist in the development of injury mitigation strategies. Both the free flight trajectory of the rider and the rider's trajectory as influenced by interaction with the motorcycle and collision partner are examined. Rider trajectories in full scale crash testing and real world motorcycle crashes are both studied and presented. The resulting physical evidence that can be observed by an accident analyst is discussed. The application of projectile motion physics is analyzed and the necessary input parameters, such as initial launch angle, are studied. This study will assist in understanding the post-impact dynamics of a motorcyclist, and will provide useful information to analysts evaluating real world crashes.
Car occupants have a high level of mortality in road accidents, since passenger cars are the prevalent mode of transport. In 2013, car occupant fatalities accounted for 45% of all road accident fatalities in the EU. The objective of this research is the analysis of basic road safety parameters related to car occupants in the European countries over a period of 10 years (2004-2013), through the exploitation of the EU CARE database with disaggregate data on road accidents. Data from the EU Injury Database for the period 2005 - 2008 are used to identify injury patterns, and additional insight into accident causation for car occupants is offered through the use of in-depth accident data from the EC SafetyNet project Accident Causation System (SNACS). The results of the analysis allow for a better understanding of the car occupants' safety situation in Europe, thus providing useful support to decision makers working for the improvement of road safety level in Europe.
Whiplash injuries are characterized by the high variability of its symptoms and by the subjectivity of its diagnosis, which sometimes leads to frauds perpetrated by victims of rear-end impacts. It is estimated that whiplash injuries cost annually about 10.000 million Euros in Europe. Therefore, the aim of this study was to investigate the influence of the dynamics of the accident in which the victim was involved in the probability of development of whiplash associated injuries. In the presented methodology, first an accident reconstruction is performed where the dynamics of the accident is determined. This is carried out using the software PC-Crash, police and insurance companies' data. Then biomechanical injuries criteria related with whiplash injuries are evaluated. For the evaluation of the probability of having whiplash injuries, the Neck Injury Criterion (NIC) of the victim and the mean acceleration of the vehicle were evaluated. Then, with medical reports, the results of the accident reconstruction are correlated with the reported injuries. Some examples are presented. The results obtained indicate that the study of the dynamics of the road accidents in which the victims were involved could be used as an auxiliary of the prognosis of whiplash injuries and is important for a precise diagnosis of this type of injuries.
Still correlated with high mortality rates in traffic accidents traumatic aortic ruptures were frequently detected in unprotected car occupants in the early years. This biomechanical analysis investigates the different kinds of injury mechanisms leading to traumatic aortic injuries in todays traffic accidents and how the way of traffic participation affects the frequency of those injuries over the years. Based on GIDAS reported traffic accidents from 1973 to 2014 are analyzed. Results show that traumatic aortic injuries are mainly observed in high-speed accidents with high body deceleration and direct load force to the chest. Mostly chest compression is responsible for the load direction to the cardiac vessels. The main observed load vector is from caudal-ventral and from ventral solely, but also force impact from left and right side and in roll-over events with chest compression lead to traumatic aortic injuries. Classically, the injury appeares at the junction between the well-fixed aortic arch and the pars decendens following a kind of a scoop mechanism, a few cases with a hyperflexion mechanism are also described. In our analysis the deceleration effect alone never led to an aortic rupture. Comparing the past 40 years aortic injuries shift from unprotected car occupants to today's unprotected vulnerable road users like pedestrians, cyclists and motorcyclists. Still the accident characteristics are linked with chest compression force under high speed impact, no seatbelt and direct body impact.
While cyclists and pedestrians are known to be at significant risk for severe injuries when exposed to road traffic accidents (RTAs) involving trucks, little is known about RTA injury risk for truck drivers. The objective of this study is to analyze the injury severity in truck drivers following RTAs. Between 1999 and 2008 the Hannover Medical School Accident Research Unit prospectively documented 43,000 RTAs involving 582 trucks. Injury severity including the abbreviated injury scale (AIS) and the maximum abbreviated injury scale (MAIS) were analyzed. Technical parameters (e.g. delta-v, direction of impact), the location of accident, and its dependency on the road type were also taken into consideration. The results show that the safety of truck drivers is assured by their vehicles, the consequence being that the risk of becoming injured is likely to be low. However, the legs especially are at high risk for severe injuries during RTAs. This probability increases in the instance of a collision with another truck. Nevertheless, in RTAs involving trucks and regular passenger vehicles, the other party is in higher risk of injury.
In-depth accident investigation offers many advantages for the analysis and comprehension of crash mechanisms. IFSTTAR makes such investigations since 1992 without interruption. The corresponding database contains more than 1200 accident case studies. Currently, in-depth accident investigation is one of the best ways to determine the speed or cars involved in accidents. This paper first presents the methods used for accident investigation and for accident kinematic reconstruction. Then, in order to illustrate the interest and possible applications of such accident data, it shows some results from a recent study based on the IFSTTAR in-depth accident study programme (IDAS) and dealing with the link between travelling speed and accident risk.
For the avoidance of traffic accidents by means of advanced driver assistance systems the knowledge of failures and deficiencies a few seconds before the crash is of increasing importance. This information e.g. is collected in the German accident survey GIDAS by an interview derived from the ACAS methodology. However to display the whole range of accident causation factors additional information is needed on enduring factors of the system components "human", "infrastructure" and "machine". On the strategic level these accident moderating factors include long term influences such as medical preconditions or a general higher risk taking behavior as well as influences on the immediate conflict level such as an aggressive response to a perceived previous traffic conflict. This study was conducted to examine the feasibility of collecting such causation information in the scope of an in-depth accident investigation like GIDAS. Due to the comprehensive amount of information necessary to estimate the moderating factors the collection of the information is distributed to different methods. 5 cases of real world crashes have been investigated where information was collected on-scene and retrospective by interviews. The identified moderating factors of the accidents and the method for collecting the information are displayed.
Motorcycle crashes in Austria: Analysis of causes and contributing factors based on in-depth data
(2017)
From CEDATU, the in-depth accident database run by the Vehicle Safety Institute at Graz University of Technology, a representative sample of 101 crashes involving at least one motorcycle was selected. The analysis focused on causes for crashes as well as on contributing factors, but also included parameters of road, riders and vehicles. Own riding speed and "unexpectable action by another road user" were the most frequent causes for accidents. Inappropriate safety distance or delayed reaction were frequent, both as causation factors and as contributing factors. Infrastructure issues never cause an accident, but they are very frequent as contributing factors; road geometry and road guidance are by far most frequent among these. This paper also discusses accidents by type and other parameters (e.g. injury severity by body region, collision speed, age and others), and compares accident causes to previous studies as well as the police reported accident statistics.
Recently, EuroNCAP updated the upper legform test protocols. The main objective of this study is to establish the upper legform test in KIDAS (Korean In-depth Accident Study) taking into account domestic pedestrian accident data as well as anthropometric data to protect elderly pedestrians whose average height and weight is much smaller and lighter than other age groups, especially compared to Europeans. Therefore 230 cases of pedestrian accidents from KIDAS were investigated to explore the injury severity of body regions as well as age related injury patterns. Injuries of all body regions were examined, with a special focus on injuries of abdomen and pelvic area. On the other hand, in order to explore Korea's pedestrian accident environment, national police data and KIDAS (Korean In-depth Accident Study) data were compared. The results should be taken into account in future analyses and possible improvements, such as regulations and KNCAP test protocols, of the pedestrian safety policy in Korea.
Although the annual traffic accident statistics published by the national police is available in public, the detailed traffic accident data has not been released in Korea. Recently the Ministry of Land, Infrastructure and Transport recognized the importance of in-depth accident data to enhance road traffic safety and initiated a research project to establish a collection of the detailed accident data. The main objective of the project is a feasibility study to establish KIDAS (Korea In-Depth Accident Study). Within this project, three university hospitals which are located in mid-size cities have been selected to collect accident data. Annually, more than 500 cases of accidents have been collected from the in-patient's interviews and diagnosis. Unlike GIDAS (German In-Depth Accident Study), currently on-site investigation can"t be performed by the Korean police. The only available data is patient medical records, patient's description of accident circumstances and the damaged vehicle. Occasionally the police provide the accident investigation reports containing very brief information on accident causation and vehicle safety. In a first step, the concept of KIDAS is to adopt the format of iGLAD (Initiative for the Global Harmonization of Accident Data) for harmonization. Since the currently collected accident information is extremely limited compared with GIDAS, the other sources of data and calculations such as KNCAP vehicle data, pc-crash simulations, vehicle registration information, insurance company data are utilized to complete the iGLAD template. Results from KIDAS_iGLAD and the cases of assessment of active safety devices such as AEBS, ESC, and LDWS will be evaluated.
Road accidents are typically analyzed to address influences of human, vehicle, and environmental (primarily infrastructure) factors. A new methodology, based on a "Venn diagram" analysis, gives a broader perspective on the probable factors, and combinations of factors, contributing both to the occurrence of a crash and to sustaining injuries in that crash. The methodology was applied to 214 accidents on the Mumbai-Pune expressway. Factors contributing to accidents and injuries were addressed. The major human factors influencing accidents on this roadway were speeding (30%) and falling asleep (29%), while injuries were primarily due to lack of seat belt use (46%). The leading infrastructure factor for injuries was impact with a roadside manmade structure (28%), and the main vehicle factor for injuries was passenger compartment intrusion (73%). This methodology can help identify effective vehicle and infrastructure-related solutions for preventing accidents and mitigating injuries in India.
Injury severity of e.g. pedestrians or bikers after crashes with cars that are reversing is almost unknown. However, crash victims of these injuries can frequently be seen in emergency departments and account for a large amount of patients every year. The objective of this study is to analyze injury severity of patients that were crashed into by reversing cars. The Hannover Medical School local accident research unit prospectively documented 43,000 road traffic accidents including 234 crashes involving reversing cars. Injury severity including the abbreviated injury scale (AIS) and the maximum abbreviated injury scale (MAIS) was analyzed as well as the location of the accident. As a result 234 accidents were included into this study. Pedestrians were injured in 141 crashes followed by 70 accidents involving bikers. The mean age of all crash victims was 57 -± 23 years. Most injuries took place on straight stretches (n = 81) as well as parking areas (n = 59), entries (n = 36) or crossroads (n = 24). The AIS of the lower extremities was highest followed by the upper extremities. The AIS of the neck was lowest. The mean MAIS was 1.3 -± 0.6. The paper concludes that the lower extremities show the highest risk to become injured during accidents with reversing cars. However, the risk of severe injuries is likely low.
Analysis of pedestrian leg contacts and distribution of contact points across the vehicle front
(2015)
Determining the risk to pedestrians that are impacted by areas of the front bumper not currently regulated in type-approval testing requires an understanding of the target population and the injury risk posed by the edges of the bumper. National statistics show that approximately 10% of all accident casualties are pedestrians, with 20% to 30% of these pedestrian casualties being killed or seriously injured. However, the contact position across the front of the bumper is not recorded in national statistics and so in-depth accident databases (OTS, UK and GIDAS, Germany) were used to examine injury risk in greater detail. The results showed that some injury types and severities of injuries appear to peak around the bumper edges. Although there are sometimes inconsistencies in the data, generally there is no evidence to suggest that the edges of the bumper are less likely to be contacted or cause injury.
This study aimed at prediction of long bone fractures and assessment of lower extremity injury mechanisms in real world passenger car to pedestrian collision. For this purpose, two pedestrian accident cases with detail recorded lower limb injuries were reconstructed via combining MBS (Multi-body system) and FE (Finite element) methods. The code of PC Crash was used to determine the boundary conditions before collision, and then MBS models were used to reproduce the pedestrian kinematics and injuries during crash. Furthermore, a validated lower limb FE model was chosen to conduct reconstruction of injuries and prediction of long bone fracture via physical parameters of von Mises stress and bending moment. The injury outcomes from simulations were compared with hospital recorded injury data and the same long bone fracture patterns and positions can be observed. Moreover, the calculated long bone fracture tolerance corresponded to the outcome from cadaver tests. The result shows that FE model is capable to reproduce the dynamic injury process and is an effective tool to predict the risk of long bone fractures.
Cycling supports the independence and health of the aging population. However, elderly cyclists have an increased injury risk. The majority of injured cyclists is victim of a single-sided accident, an accident in which there is no other party involved. The aim of the project "Safe and Aware on the bicycle" is to develop guidelines for an advisory system that is useful in preventing single-sided accidents. This system is able to support the elderly cyclist; enabling the cyclist to timely adapt his cycling behaviour and improve cycling safety and comfort. For the development of such advisory system the causes of singles accidents and the wishes of the elderly cyclist must be known. First step to obtain this insight was a literature survey and an GIDAS research. Unfortunately accidentology research with GIDAS did not give the full understanding of the pre-crash situations and (especially the behaviour related) factors leading to the accident. The second step was consultation of elderly cyclist through a questionnaire (n=800), in-depth interviews (n=12) and focus group sessions (n=15). This offered complementary information and a much better understanding of the behavioural aspects. Results concern the behaviour in traffic and identify specific physical (i.e. problems looking backwards over the shoulder) and mental issues. Furthermore, the needs and wishes for support in specific cycling situations were identified. In conclusion; The GIDAS results together with the information obtained contacting the elderly cyclists enabled setting up requirements for an advisory system, which is useful in preventing single-sided accidents.
Since a number of human models have been developed it appears sensible to use these models also in the accident analysis. Especially the understanding of injury mechanisms and probably even injury risk curves can be significantly improved when interesting accidents are reconstructed using human body models. However, an important limitation for utilising human models for accident reconstruction is the effort needed to develop detailed FE models of the accident partners or to prepare the human model reconstruction by running physical accident reconstructions. The proposed approach for using human models for accident reconstruction is to use simplified and parametric car models. These models can be adapted to the crash opponents in a fast and cost effective way. Although, accuracy is less compared to detailed FE models, the relevant change in velocity can be simulated well, indicating that the computation of a detailed crash pulse is not needed. Two frontal impact test accidents that were reconstructed experimentally and using the parametric car models are indicating sufficient correlation of the adapted parametric car models with the full scale crash reconstructions. However, further developments of the parametric models to be capable for the use in lateral impacts and rear impacts are needed. For the PC Crash simulation runs the output sampling rate is too large to allow sufficient analysis. In addition the performance appears to be too general.
This study aimed at developing an injury estimation algorithm for AACN technologies for Germany and compared them to findings based on Japanese data. The data to build and to verify the algorithm was obtained from the German in-depth Accident Database (GIDAS) and split into a training and a validation dataset. Significant input variables and the generalized linear regression model to predict severe injuries (ISS>15) were selected to maximize area under the receiver operating characteristic curve (AUC). Probit regression with the input parameter multiple impact, delta v, seatbelt use and impact direction gave the largest AUC of 0.91. Sensitivity of the algorithm was validated at 90% and specificity at 76% for an injury risk threshold of 2%. It appears that no major differences between Japan and Germany exist for injury estimation based on delta v and impact direction. However, far side impact and multiple crash events appear to be associated with a larger risk increase in the German data.
This study aimed at comparing head Wrap Around Distance (WAD) of Vulnerable Road User (VRU) obtained from the German in-depth Accident Database (GIDAS), the China in-depth Accident Database (CIDAS) and the Japanese in-depth Accident Database (ITARDA micro). Cumulative distribution of WAD of pedestrian and cyclist were obtained for each database (AIS2+) showing that WAD of cyclists were larger than the ones of pedestrians. Comparing three regions, the 50%tile WAD of GIDAS was larger than that of both Asian accident databases. Using linear regression that might predict WAD of pedestrians and cyclists from Impact speed and VRU height, WADs were calculated to be 206cm/219cm (Pedestrian/Cyclist) for GIDAS, 170cm/192cm for CIDAS and 211cm/235cm for ITARDA. In addition, this study may be helpful for reconsideration of WAD measurement alignment between accident reconstruction and test procedures.
Pedestrians represent about 20% of the overall fatalities in Europe- road traffic accidents. In this paper a methodology is proposed to understand why the numbers are so high, especially in the south of Europe and particularly in Portugal, . First a detailed statistical analysis using Ordinal Logistic Regression model (OLR) was applied to the gathered data from all Portuguese accidents with victims in the period 2010-2012. In a second stage accident reconstruction computational techniques using pedestrian biomechanical models are used to evaluate the accident conditions that lead to the injuries, such as the speed and the impact location. For biomechanical injury criterions, the AIS (Abbreviated Injury Scale), the HIC (Head Injury Criterion) and other injury criterions based on the resulting accelerations in the pedestrian's body are used. The statistical model reported that there were several predictors that significantly influenced the pedestrian injury severity in the event of a road accident, such as Pedestrian's age, Pedestrian's gender, Vehicle Design/Category or Driver's gender. The use of injury scales and biomechanical criterions in in-depth investigation of road accidents, such as AIS, can significantly improve the quality of the reconstruction process.
Today's volumes of traffic require more and more responsibility from each individual road user in their interactions. Those who drive motor vehicles have the singular obligation to minimise the risk of accidents and hence the severity of injuries, particularly with a view to the most vulnerable road users such as motor bikes, bikes and pedestrians. Since responsible and pro-active driving depends first and foremost on the visual information relayed by our eyes and the visual channel this requires good command of the traffic and all-round visibility from our driver's seat. Granted that human error can never be fully excluded, improving visibility around the car is nevertheless an urgent priority. To do so, we need to rate visibility in the most realistic driving situations. Since the existing visibility metrics and methodology are not applicable to real-life driving situations, this study aimed at developing a new visibility rating methodology based on real-life accident scenarios. On the basis of the cases documented by the accident research project, this study analysed criteria indicative of diminishing visibility on the one hand and revealing some peculiarities in connection with the visibility issue on the other. Based on the above, the project set out to develop a rating methodology allowing to assess all-round visibility in various road situations taking into account both driver and road geometries. In this context, the assessment of visibility while turning a corner, crossing an intersection and joining traffic on a major road (priority through route) is of major importance. The first tests have shown that critical situations can be avoided by adapting the relevant geometries and technical solutions and that significant improvements of road safety can be derived therefrom.
For the estimation of the benefit and effect of innovative Driver Assistance Systems (DAS) on the collision positions and by association on the accident severity, together with the economic benefit, it becomes necessary to simulate and evaluate a variety of virtual accidents with different start values (e.g. initial speed). Taken into account the effort necessary for a manual reconstruction, only an automated crash computation can be considered for this task. This paper explains the development of an automated crash computation based on GIDAS. The focus will be on the design of the virtual vehicle models, the method of the crash computation as well as exemplary applications of the automated crash computation. For the first time an automated crash computation of passenger car accidents has been realized. Using the automated crash computation different tasks within the field of vehicle safety can be elaborated. This includes, for example, the calculation of specific accident parameters (such as EES or delta-V) for various accident constellations and the estimation of the economic benefit of DAS using IRFs (Injury Risk Functions).
The project UR:BAN "Cognitive assistance (KA)" aims at developing future assistance systems providing improved performance in complex city traffic. New state-of-the-art panoramic sensor technologies now allow comprehensive monitoring and evaluation of the vehicle environment. In order to improve protection of vulnerable road users such as pedestrians and cyclists, a particular objective of UR:BAN is the evaluation and prediction of their behaviour and actions. The objective of subproject "WER" is development support by providing quantitative estimates of traffic collisions at the very start and predict potential in terms of optimized accident avoidance and reduction of injury severity. For this purpose an integrated computer simulation toolkit is being devised based on real world accidents (GIDAS as well as video documented accidents), allowing the prediction of potential effectiveness and future benefit of assistance systems in this accident scenario. Subsequently, this toolkit may be used for optimizing the design of implemented assistance systems for improved effectiveness.
Introduction: The method of causation analysis applied under the German accident survey GIDAS, which is based on Accident Causation Analysis System (ACAS) focuses on an on-scene data collection of predominantly directly event-related causation factors which were crucial in the accident emergence as situational resulting events and influences. The paradigm underlying this method refers to the findings of the psychological traffic accident research that most causally relevant features of the system components human, infrastructure and vehicle technology are found directly in the situation shortly before the accident. This justifies the survey method which is conducted directly at the accident (on-scene), shortly after the accident occurrence (in-time) with the detection of human-related causes (in-depth). Human aspects of the situation analysis that interact and influence the risk situations shortly before the collision are reported as errors, lapses, mistakes and failures in ACAS in specific categories and subcategories. Thus methodically ACAS is designed primarily for the collection of accident features on the level of operational action, which certainly leads to valid findings and behavioral causes of accidents. The enhancement by means of Moderating Conditions concerns the pre-crash phase in different levels: strategical, tactical and operational.
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