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The Decision Support System (DSS) is one of the key objectives of the European co-funded research project SafetyCube in order to better support evidence-based policy making. Results will be assembled in the form of a DSS that will present for each suggested road safety measure: details of risk factor tackled, measure, best estimate of casualty reduction effectiveness, cost-benefit evaluation and analytic background. The development of the DSS presents a great potential to further support decision making at local, regional, national and international level, aiming to fill in the current gap of comparable measures effectiveness evaluation. In order to provide policy-makers and industry with comprehensive and well-structured information about measures, it is essential that a systems approach is used to ensure the links between risk factors and all relevant safety measures are made fully visible. The DSS is intended to become a major source of information for industry, policy-makers and the wider road safety community.
In Germany road tunnels on major roads which are longer than 400 m have to be monitored permanently. For that purpose the tunnels are equipped with a multitude of monitoring and detection systems whose data and messages are transmitted to tunnel control centres. Due to the higher traffic density, the increasing number of tunnels to be monitored and road users" demand of higher safety and security levels, the strains on operating staff of tunnel control centres have continuously been growing. Therefore, innovative approaches have been developed in two recent German research projects: RETISS " Real Time Security Management System, and ESIMAS " Real-time Safety Management System for road Tunnels. Both systems are designed to allow faster and more efficient reaction of tunnel operators in order to maintain the capacity and availability of transport infrastructures but also to improve the safety and security of road users.
The current paper reports on the results of a pilot study aiming to investigate the effect of mobile telephone use on the driving performance of 5 amateur and 5 professional drivers. Their driving acuity was tested through a driving simulator. Analysis and interpretation of the results occurred comparing the drivers' driving performance while talking, reading messages and writing a message on the mobile phone (intervention time) with the drivers' driving performance engaged in no activity (control time). The variables affected by the mobile phone were the "steering", the "lane offset" and the "duration of lane offset". Moreover, the drivers involved in a car crash in the last five years appeared to differ from those who were not involved in a crash in both "lane offset" and "following distance". The results of this pilot study will inform the design of a large experimental study on 50 professional and 50 amateur drivers.
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.
Ruptures and dissections of the thoracic and abdominal aortic vessel caused by traffic accidents are rare but potentially life-threatening injuries. They can occur by blunt trauma via seat belt or dashboard injury. The study aimed at evaluating the overall mortality, morbidity, neurological disorders, and differences in operative procedures of open repair and stenting. It shows that, with a change and improvement in diagnostic tools and surgical approach, mortality and morbidity of blunt aortic injuries were significantly reduced. Still an immediate life-threatening injury early diagnosis via multiple-slice and scans and surgical repair with minimally invasive stents showed excellent short-time results for selected patients.
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.
The main focus of the benefit estimation of advanced safety systems with a warning interface by simulation is on the driver. The driver is the only link between the algorithm of the safety system and the vehicle, which makes the setup of a driver model for such simulations very important. This paper describes an approach for the use of a statistical driver model in simulation. It also gives an outlook on further work on this topic. The build-up process of the model suffices with a distribution of reaction times and a distribution of reaction intensities. Both were combined in different scenarios for every driver. Each scenario has then a specific probability to occur. To use the statistical driver model, every accident scene has to be simulated with each driver scenario (combinations of reaction times and intensities). The results of the simulations are then combined regarding the probabilities to occur, which leads to an overall estimated benefit of the specific system. The model works with one or more equipped participants and delivers a range for the benefit of advanced safety systems with warning interfaces.
Event data recorders (EDRs) are a valuable tool for in-depth investigation of traffic accidents. EDRs are installed on the airbag control module (ACM) to record vehicle and occupant information before, during, and after a crash event. This study evaluates EDR characteristics and aims at better understanding EDR performance for the improvement of accident reconstruction with more reliable and accurate information regarding accidents. The analysis is based on six crash tests with corresponding EDR datasets.