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.
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.
Mit Fokus auf Nordrhein-Westfalen (NRW) wird das urbane NO2-Problem umrissen. Um die Jahresgrenzwerte einzuhalten, sind beispielsweise in allen Straßenschluchten in NRW Reduktionen nötig. Die Europäische Kommission hat gegen mehrere Mitgliedsstaaten, darunter Deutschland, Vertragsverletzungsverfahren wegen der Überschreitung von NO2-Grenzwerten eröffnet. Dargestellt werden die Langzeittrends bezüglich der gemessenen Abnahme bei der Stickoxidbelastung. Potenzielle Maßnahmen können hinsichtlich ihrer möglichen Wirkungen durch den Einsatz von Modellen abgeschätzt werden, zum Beispiel Umweltzonen, Fahrverbote, Elektrofahrzeuge. Die Ergebnisse der Messungen und Modellrechnungen werden dargestellt und kritisch beleuchtet. Als Fazit ergibt sich, dass das urbane NO2-Problem nicht einfach zu lösen ist, Minderungen der NOx-Emissionen spiegeln sich nicht in der gleichen Größenordnung in der Abnahme der NO2-Belastung wieder. Bei zusätzlich wirksamen Maßnahmen wie beispielsweise einem höheren Anteil von Elektrofahrzeugen fehlt die (schnelle) praktische Umsetzbarkeit. Eine Kombination aus lokalen, regionalen und europaweiten Maßnahmen ist nötig, um das Problem zu lösen.
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.
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 Traffic Accident Research Institute at University of Technology Dresden investigates about 1,000 accidents annually in the area around and in Dresden. These datasets have been summarized and evaluated in the GIDAS (German Accident In-Depth Study) project for 13 years. During the project it became apparent that the specific traffic situation of a covert exit of a passenger car and an intersecting two-wheeler involves a high risk potential. This critical situation develops in a large part due to the lack of visibility between the driver and the intersecting bike. In this paper the accident avoidance potential of front camera systems with lateral field of view, which allows the driver to have an indirect sight into the crossing street area will be presented.
Enhanced protection of pedestrians and cyclists remains on the focus. Besides infrastructural and behavioral aspects it is necessary to exploit technical solutions placed on motorized vehicles. Accident research needs reliable data as well as national road accident statistics. Changing the view on seriously injured road users is one of the challenges which will substantially contribute to the optimization on future traffic safety. The missing accuracy in the definition of personal injury has a detrimental effect on making cost efficient road safety policy which is not only focused on fatal accidents. The European commission requested that, starting in 2015, all EU member states provide more detailed data on the injury status of road casualties, with special regard to the group of seriously injured. Conventional accident data will always be essential. But to obtain detailed data about driver behavior in real traffic situations further data sources are required. These could be EDR data, data from electronic control units, data from traffic surveys and traffic counting, naturalistic diving studies and field operational tests. Gaining insight into normal as well as critical driver behavior will enable accident researchers to deduct functions estimating the increase or decrease of accident risk associated with certain behaviors or vehicle functions. Also with view to the introduction of highly automated driving functions in the future such data is urgently needed. Computer simulation based tools to estimate the benefits of active safety systems are another step on the way towards the safety assessment of automated driving. It is now the duty of the scientific community to ask the right questions, to develop a methodology and to merge all these data sources into a common framework for the assessment of future traffic safety innovations.
SEEKING is looking for answers regarding electric powered bicycles and their relation to traffic safety issues. Does a cyclist need "E"? Is it as risky as riding a moped or are E-bikes creating conflicts with other cyclists? The project described herein, funded by the Austrian Ministry of Transport, has the aim of seeking answers to these hot topics. The SEEKING-team shows an in-depth investigation of vehicle dynamic sensing, together with subjective feedback of test riders to detect similarities and differences between conventional cycling and E-biking. Following an overview on the international status quo, measurement runs and their analyses are performed to find a set of preventative measures to make (E-)biking safer. A specific focus is the detection of curve handling, stopping and acceleration phases as well as conflict studies on course-based test rides and "real world" tests on cycling paths (naturalistic riding).
Ausgehend von den rechtlichen Grundlagen für die Luftreinhaltung sowie den Grenzwertfestlegungen für Feinstaub (PM10) sowie Stickoxide (NO2) wird auf die heutige Luftqualität in Städten mit Schwerpunkt Stuttgart eingegangen. Dargelegt werden die festgestellten Überschreitungen bei den Grenzwerten für PM10 und NO2. Eingegangen wird auf die Maßnahmen zur Reduzierung der Luftbelastung in Stuttgart und die Wirkungen in Bezug auf die Senkung der Grenzwert-Übersschreitungen beziehungsweise Jahresmittelwerte von PM10 und NO2 an den Hotspot-Stationen "Am Neckartor" und "Hohenheimer Straße". Abschließend wird ein perspektivischer Ausblick gegeben: obwohl die Luftsituation in den Städten kontinuierlich besser geworden ist, gibt es an stark befahrenen städtischen Straßen weiterhin Grenzwertüberschreitungen. Die EU-Vertragsverletzungsverfahren machen weitere Maßnahmen notwendig. Die Städte brauchen praxiserprobte Maßnahmen und keine langfristigen, kostspieligen Pilotversuche mit unsicherem Ausgang.
Vorgestellt werden Ergebnisse aus der Untersuchung "Vergleich verschiedener Modellierungsprogramme zur Berechnung von Luftschadstoffen". Die Untersuchung wurde begleitend zu der Pilotstudie "NO2-Reduktion an Ti02-dotierten Lärmschutzwänden (LSW) an der A1" durchgeführt. Projektziel war der Vergleich von drei Ausbreitungsmodellen sowie die Auswahl eines geeigneten Modells für ein zu entwickelndes Online-Monitoring-System. Es wurde festgestellt, dass sich die Modellergebnisse infolge der Umsetzung kleinräumiger Details unterscheiden sowie dass alle Modelle lediglich geringe NOx-Minderungen in Folge der katalytischen Oberflächenbeschichtung anzeigen. In den numerischen Modellen wird die photokatalytische Wirkung der Ti02-beschichteten Lärmschutzwand über einen Depositionsprozess berücksichtigt. Unter Berücksichtigung der Hintergrundbelastung und der NOx-NO2-Umwandlung würde sich die Wirkung des Katalysators im Maximum auf weniger reduzieren. Die Messungen zeigten keine eindeutige Wirkung bezüglich der Immissionskonzentrationen im Bereich der beschichteten beziehungsweise unbeschichteten LSW an.