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Electronic Stability Program (ESP) aims to prevent the lateral instability of a vehicle. Linked to the braking and powertrain systems, it prevents the car from running wide on a corner or the rear from sliding out. It also helps the driver control his trajectory, without replacing him, in the case of loss of control where the driver is performing an emergency manoeuvrer (confused and exaggerated steering wheel actions). A new ESP function optimizes ESP action in curves with hard under steering (situations in which the front wheels lose grip and the vehicle slides towards the outside of the curve). A complementary feature prevents the wheels from spinning when pulling away and accelerating. The name given to the ESP system varies according to the vehicle manufacturer, but other terms include: active stability control (ASC), automotive stability management system (ASMS), dynamic stability control (DSC), vehicle dynamic control (VDC), vehicle stability control (VSC) or electronic stability Control (ESC). This paper proposes an evaluation of the effectiveness of ESP in terms of reduction of injur accidents in France. The method consists of 3 steps: - The identification, in the French National injury accident census (Gendarmerie Nationale only), of accident-involved cars for which the determination of whether or not the car was fitted with ESP is possible. A sample of 1 356 cars involved in injury accidents occurred in 2000, 2001, 2002 and 2003 was then selected. But we had to restrict the analysis to only 588 Renault Lagunas. - The identification of accident situations for which we can determine whether or not ESP is pertinent (for example ESP is pertinent for loss of control accidents whilst it is not for cars pulling out of a junction). - The calculation, via a logistic regression, of the relative risk of being involved in an ESPpertinent accident for ESP equipped cars versus unequipped cars, divided by the relative risk of being involved in a non ESP-pertinent accident for ESP equipped cars versus unequipped cars. This relative risk is assumed to be the best estimator of ESP effectiveness. The arguments for such a method, effectiveness indicator and implicit hypothesis are presented and discussed in the paper. Based on a few assumptions, ESP is proved to be highly effective. Currently, the relative risk of being involved in an ESP pertinent accident for ESP-equipped cars is lower (-44%, although not statistically significant)rnthan for other cars.rn
In order to improve the protection of children transported in cars, within the CHILD programme (GR3D-CT2002-00791) real world road accidents are thoroughly analysed and then reconstructed in laboratory. Prior to comparing injury severities of real victims to physical parameter values measured on the dummies, the quality of the reconstructions is evaluated by experts who use their experience based on the investigation of numerous and various accidents. This paper presents a new tool aiming at better evaluating and validating accident reconstructions. It is based on statistical evaluation of vehicle deformations which gives weighing factors for every part of the car body structure finally leading to a specific Reconstruction Quality Score (RQS indicator). Furthermore, the reliability of this score, depending on the number of measured points, can be established. This tool includes a function aiming at adjusting the speed for a further reconstruction and at defining the launching speed and the pulse shape for complementary sled tests. Finally, the functions of the RQS software and database are presented.
This contribution introduces a number of psychological methods of analysis that are based on the practice-oriented collection of information directly at the site of an accident and that allow for an analysis and coding of the accident causes. Investigation examples and examples of the data combinations with basic medical and technical data are outlined. Objective of the collection is the inter-disciplinary investigation of human factors in the causes of accidents ("human-factor-analysis"). The psychological data are incorporated according to an integrative model for accident causes based on empiric algorithms in the data base of the accident research, where the clustered evaluation potential of comprehensive factors of the accident development can be illustrated. The central theoretical concept for the basic model of the progress of the accident from a psychological point of view comprises psychological indicators for the evaluation of the site of the accident for the analysis of the perception conditions as well as a classification of the gleaned data into the accident progress model according to chronological and local criteria. Perception conditions, action intentions and executions as well as conditions limiting perception and actions are acquired, using a questionnaire for persons involved in an accident, and are also integrated into the data structure concerning weighted feature characteristics as well as combined with other relevant features. Suitable systematization tools for the collection and coding of psychological accident development parameters have to be provided, which require primarily a model image of the corresponding processes from the persons involved in the accident (perceptions, expectations, decisions, actions). The interactive accident model contains components of the models by KÜTING 1990, MC DONALD 1972, SURREY 1969 and RASMUSSEN 1980. Based on the inter-action of the three partial systems "person", "vehicle" and "environment", the first step is the assessment of the situation by the persons involved in the accident. This is dependent on the personal attitudes and motives, on experiences and expectations concerning the progress of the situation. Subsequently, data concerning the manner of the coping with the ambiguous state as well as with the instable state (emergency reaction immediately before the accident occurs) are collected. The factors relating to the persons involved in the accident are gathered on several levels using corresponding questionnaires. The coding of the found and collected characteristics is conducted in a multidimensional evaluation relating to the technical results of the accident reconstruction and of the psychological classification, which are subsequently integrated in coded form into the data base of the accident research. The result of this analysis is a description of the development of the accident depicted on a chronological vector from a perception and decision theoretical perspective. This is explained in detail using exemplary cases.
Road safety is a major preoccupation of the European Commission and the road transport industry and depends on numerous significant factors. In order to improve road safety and to plan effective safety improvement actions for truck transport, we must first identify the problems to be addressed, i.e. what are the main causes of truck accidents. The ETAC project, initiated by the European Commission and the IRU, was launched in order to set up a heavy goods vehicle accident causation study across European countries to identify future actions which could contribute to the improvement of road safety. The results will be based on a detailed analysis of truck accident data collected in seven European countries according to a common methodology which has been elaborated through numerous national and European projects. This paper describes the common methodology used to collect the information on the scene of the accident and to analyse the data so that the reconstruction of the crash events may be carried out. CEESAR proposes a methodology using its experience gained from over 10 years of accident data collection. This methodology is based on an in-depth investigation of the parameters involved in-an accident and linked to the driver, the vehicle, the road and their environment. In-depth investigation requires accident investigator presence on the scene of the accident in order to collect volatile information such as marks on the road, weather conditions, visibility, state and equipment of the vehicle, driver interview. Later, passive and active information is gathered, either at the hospital for the driver, at the garage for the vehicle or on the spot for the road geometry. A reconstruction carried out with the help of specific software and the analysis of the data collected and calculated enables the identification of the main causes of the accident and the future actions to plan in order to improve road safety as regards truck traffic.
In the last years various new driver information and driver assistance systems made their way into modern vehicles and there are yet countless systems underway. However, expenses for both, the development and the construction of these systems are tremendous. Therefore the interest of evaluating systems keeps growing steadily, not only regarding the results of systems developed in the last years but also regarding system ideas. Only if at least a rough benefit estimation is given, the industry can decide which development should be supported. However, there is still a lack of transparency of possible and useful methods for these kinds of estimations. These were analyses and structured in this study.
Over the past two decades the popularity of consumer crash test programs, commonly referred to as New Car Assessment Programs (NCAP), has grown across the world. They are popular among government regulators as they afford a means of promoting safety innovations and levels of vehicle performance beyond those dictated by national standards. They also fulfill the demand for information regarding the safety ranking of vehicles among consumers contemplating the purchase of a new vehicle. There is no question that consumer crash test programs greatly influence vehicle design changes as well as accelerate the fitment of new safety features. The extent to which these changes can be expected to reduce serious and potentially fatal injuries will be influenced by how well the testing protocols and associated rating schemes correctly reflect the nature of the residual safety problem they seek to address. Drawing on data contained primarily in the US National Automotive Sampling System (NASS), the field relevance of current and proposed testing and rating protocols addressing frontal crash test protection is examined. Emphasis is placed on examining how accurately injury rates computed from the dummy responses measured in consumer crash tests correspond to actual injury rates observed in the field. Additional data from Canadian field investigations and US databases such as the National Motor Vehicle Crash Causation Survey (NMVCCS) are examined to see how well frontal airbag firing times, crush pulse durations and other determinants of injury are replicated in consumer testing protocols. This portion of the analysis draws on data obtained from Event Data Recorders (EDR) in both field collisions and staged tests of the same vehicle model. Vehicle rankings and overall frontal crash test ratings were found to be particularly sensitive to the choice of injury risk functions employed in the test. This was particularly true in the case of injury risk functions used to assess neck injury potential. Neck injury risk derived from Nij was found to show the least agreement with the field. Agreement between field chest injury rates and those derived from crash tests was improved considerably when chest injury risk functions for "older" occupants were employed. The paper concludes with a discussion of how different current testing protocols could be improved to enhance their field relevance.
The overall purpose of the ASSESS project is to develop a relevant and standardised set of test and assessment methods and associated tools for integrated vehicle safety systems, primarily focussing on currently available pre-crash sensing systems. The first stage of the project was to define casualty relevant accident scenarios so that the test scenarios will be developed based on accident scenarios which currently result in the greatest injury outcome, measured by a combination of casualty severity and casualty frequency. The first analysis stage was completed using data from a range of accident databases, including those which were nationally representative (STATS19, UK and STRADA, SE) and in-depth sources which provided more detailed parameters to characterise the accident scenarios (GIDAS, DE and OTS, UK). A common analysis method was developed in order to compare the data from these different sources, and while the data sets were not completely compatible, the majority of the data was aligned in such a way that allowed a useful comparison to be made. As the ASSESS project focuses on pre-crash sensing systems fitted to passenger cars, the data selected for the analysis was "injury accidents which involved at least one passenger car". The accident data analysis yielded the following ranked list of most relevant accident scenarios: Rank Accident scenario 1 Driving accident - single vehicle loss of control 2 Accidents in longitudinal traffic (same and opposite directions) 3 Accidents with turning vehicle(s) or crossing paths in junctions 4 Accidents involving pedestrians The ranked list highlights the relatively large role played by "accidents in longitudinal traffic", and "accidents with turning vehicle(s) or crossing paths in junctions" (the second and third most prevalent accident scenarios, respectively). The pre-crash systems addressed in ASSESS propose to yield beneficial safety outcomes with specific regard to these accident scenarios. This indicates that the ASSESS project is highly relevant to the current casualty crash problem. In the second stage of the analysis a selection of these accident scenarios were analysed further to define the accident parameters at a more detailed level .This paper describes the analysis approach and results from the first analysis stage.
Event Data Recorder (EDR) is an additional function installed in airbag control module (ACM) to record vehicle and occupant information for a brief period of time before, during, and after a crash event. EDRs are now being installed in ACMs by several automakers in the USA and in Japan. The aim of this study is to understand the performance of EDRs for the improvement of accident reconstruction with more reliable information. In the first report of the study, data obtained from EDRs of seven vehicle types were evaluated using 2006-2007 J-NCAP (Japanese new car assessment program) full-lap frontal barrier crash tests and offset frontal deformable barrier crash tests data. For more practical standpoint, we conducted thirteen crash tests reconstructing typical real-world accidents such as single vehicle accidents with barriers or poles, car to car accidents and multi rear-end collisions focusing on Japanese typical accident types. Data obtained from EDRs are compared with data obtained from optical speed sensor, instrumented accelerometers and high speed video cameras. The velocities determined from pre-crash data of EDRs and the maximum change in velocity, delta-V, and delta-V time history data obtained from post-crash data of EDRs are analyzed. The results are as follows: - Pre-crash velocities of EDRs were very accurate and reliable. An average difference between the EDR recording values and reference speeds was 4.2% and a root mean square of the differences was 9.2%. Only two cases resulted large differences for the pre-crash velocity. Both of them were cases with braking prior to the collision. However, another test with braking resulted less difference. The braking condition may influence accuracy of pre-crash velocities. - Maximum delta-Vs obtained from the EDRs showed uncertainty of measurement in several cases in comparisons with the reliable delta-V data. The differences in maximum delta-V were more than 10% in five of twenty-five events data and more than 20% in two of twenty-five events data. An average of the all differences was about 4% and root mean square of the differences was about 11%. Especially large deformation at narrow area may influence accuracy of post-crash delta-V. - Multiple rear-end crash tests were reconstructed using EDRs data as case studies. Some EDRs recorded two events and a time gap between two events, so that these reconstruction case studies were very accurate and reliable. - If though only one of three vehicles in multiple rear end crash was equipped EDR, overview and velocities of all cars may be reconstructed using these limited EDR data. In this case study, leading car- EDR data and middle car- EDR data were valuable. However if only following car was equipped EDR, the reconstruction was not accurate
To determine whether the model "Accompanied driving from age 17" (AD17) contributes to improvement of young drivers' road safety, two large random samples of novice drivers drawn from the Central Register of Driving Licences (ZFER) held at the Federal Motor Transport Authority (KBA) were compared in terms of the rates of accident involvement and traffic offences at the start of their solo driving career. The samples comprised former participants in the AD17 model and novice drivers of the same age who had obtained a driving licence in the conventional manner immediately after their 18th birthday. Both analysis groups were contacted by post and asked to complete an online questionnaire. In response, 19,000 drivers reported on their first year of solo driving and on the occurrence of any accidents or traffic offences during this period. The analyses were repeated with two "silent" analysis groups comprising a total of 75,000 drivers, for whom any records of traffic offences were retrieved from the Central Register of Traffic Offenders (VZR), with a distinction being made between offences in connection with an accident and other offences. The AD17 model was introduced in all 16 German federal states between April 2004 and January 2008. By the end of 2009, almost one million novice drivers had participated in the model, and almost three-quarters of the target group - so-called "early beginners" who wished to commence solo driving immediately after reaching the age of 18 years - opted for the AD17 model. The phase of introduction of the model was associated with a temporary increase of around five per cent in the demand for driving licences from persons under 19 years of age. During the first year of solo driving, the rate of accident involvement for AD17 participants was 19 per cent lower and the rate of traffic offences 18 per cent lower than for drivers of the same age who had obtained their driving licence in the conventional manner. After adjustment for confounds (e.g. gender and vehicle availability), a reduction in accidents by 17 per cent and in traffic offences by 15 per cent remained as an effect attributable to the model. A comparison on the basis of the distances driven indicated 22 per cent fewer accidents and 20 per cent fewer traffic offences. The results are statistically significant and apply to both male and female drivers. The findings were confirmed in the replication study based on VZR data, with one exception: For female AD17 drivers, and here only for VZR-recorded offences excluding accidents, no significant reduction was found. On the other hand, the rate for female drivers is already lower than that of their male counterparts by three-quarters. Approximately 1,700 injury accidents were prevented by implementation of the model in 2009.
From literature well-known analyzes on risks, hazards and causes of accidents of older drivers are amended by the present study in which a comparison of the specific features of accident causes of older car drivers (older than 60 years) and of younger car drivers (under 25 years) is conducted. Mainly the question is pursued if specific errors, mistakes and lapses are predominant in the two different age groups. The analysis system ACAS (Accident Causation Analysis System) used hereby consists of a sequential system of accident causation factors from the human, the technical and the infrastructural field, whereupon for this study the influence of the human features on the accident development in two different age groups is of interest. ACAS is both an accident model and an analysis and classification system, which describes the human participation factors of an accident and their causes in the temporal sequence (from the perceptibility to concrete action errors) taking into consideration the logical sequence of individual basic functions. In five steps (categories) of a logical and temporal sequence the hierarchical system makes human functions and processes as determinants of accident causes identifiable. The methodology specifically focuses on the use in so-called "In-Depth" and "On-Scene" investigation studies. With the help of the system for each accident participant one or more of five hypotheses of human cause factors are formed and then specified by appropriate verification criteria. These hypotheses in turn are further specified by indicators in such manner that the coding of the causation factors by a code system meets the needs of database processing and are accessible to a quantitative data analysis. The first results of the descriptive comparison of the two age groups concern mainly differences in the functional levels "information admission/perception" (where the elderly drivers have more difficulties than the young ones) and "information processing/evaluation" (where the younger drivers show more problems). Concerning the cognitive function of "planning" the group of younger drivers seems to be more often involved in an accident because of excessive speed.