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Assessment of the effectiveness of Intersection Assistance Systems at urban and rural accident sites
(2015)
An Intersection Collision Avoidance System is a promising safety system for accident avoidance or injury mitigation at junctions. However, there is still a lack of evidence of the effectiveness, due to the missing real accident data concerning Advanced Driver Assistance Systems. The objective of this study is the assessment of the effectiveness of an Intersection Collision Avoidance System based on real accidents. The method used is called virtual pre-crash simulation. Accidents at junctions were reconstructed by using the numerical simulation software PC-Crashâ„¢. This first simulation is called the baseline simulation. In a second step the vehicles of these accidents were equipped with an Intersection Collision Avoidance System and simulated again. The second simulation is called the system simulation. In the system simulation two different sensors and four different intervention strategies were used, based on a time-to-collision approach. The effectiveness of Intersection Collision Avoidance System has been evaluated by using an assessment function. On average 9% of the reviewed junction accidents could have been avoided within the system simulations. The other simulation results clearly showed a change in the principal direction of force, delta-v and reduction of the injury severity.
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.
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.
The evaluation of the expected benefit of active safety systems or even ideas of future systems is challenging because this has to be done prospectively. Beside acceptance, the predicted real-world benefit of active safety systems is one of the most important and interesting measures. Therefore, appropriate methods should be used that meet the requirements concerning representativeness, robustness and accuracy. The paper presents the development of a methodology for the assessment of current and future vehicle safety systems. The variety of systems requires several tools and methods and thus, a common tool box was created. This toolbox consists of different levels, regarding different aspects like data sources, scenarios, representativeness, measures like pre-crash-simulations, automated crash computation, single-case-analyses or driving simulator studies. Finally, the benefit of the system(s) is calculated, e.g. by using injury risk functions; giving the number of avoided/mitigated accidents, the reduction of injured or killed persons or the decrease of economic costs.
In 2014 the sixth ESAR conference (Expert Symposium on Accident Research) was held in Hannover. ESAR is an international convention of experts, who analyze traffic accidents all over the world and discuss their results in this context, conducted at the Medizinische Hochschule Hannover every 2 years. It connected representatives of public authorities, engineers in automotive development and scientists and offers a forum with particular emphasis on In-Depth-Analyses of accident statistics and accident analyses. Special focus is placed on research on the basis of so-called "In-Depth-Accident-Investigations" [data collections at the sites of the accidents], which are characterized by extensive documentations of the sites of the accidents, of the vehicles as well as of the injuries, encompassing several scientific fields. ESAR aims at a multi-disciplinary compilation of scientific results and at discussing them on an international, scientific level. It is thus a scientific colloquium and a platform for exchanging information for all accident researchers. Experiences in accident prevention as well as in the complex field of accident reconstruction are stated and new research fields are added. Existing results of long-term research work in Europe, the US, Australia and Japan include different infrastructural correlations and give findings on population, vehicle population and driver characteristics, which offer a basis for recommendations to be derived and measures for increasing road safety.