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The German highway network hast o face new challenges in the near future, e.g. increasing traffic density and loads, climate change effects and new quality requirements regarding sustainability. It is necessary to come up with foresighted concepts in the present to be prepared for these challenges. Therefore it is important to adapt and enhance innovative attempts, which take changing impacts into account. One goal of these efforts is the development of adaptive systems for the provision of information and a holistic evaluation in real time. The paper describes the recent research and developments on a system for information and holistic evaluation in real time, taking into account sensor networks, evaluation procedures and their implementation in existing maintenance and inspection strategies.
The German highway network is facing new challenges in the near future. The structures have to deal with increasing traffic loads, climate change effects and new requirements regarding sustainability while they are getting older and budget cuts can be expected. To guarantee a reliable highway network, it will be vital to adapt and enhance innovative approaches. Current bridge management relies on the results of conventional bridge inspections and thus has certain limitations when it comes to insufficient load bearing capacity and other systematic weaknesses. Therefore, new approaches for real time condition assessment of critical road infrastructure elements are to be developed.
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.
The study aimed at estimating the impact of pedelecs (with an assumed higher speed than bicycles) on the traffic accident severity in Germany for different penetration rates. The analysis shows that in many real situations (68%) an electrical support of bicycles has no influence on the sequence of accident events. Taking into account a number of unreported "single bicycle accidents", the adoption of similar traffic behavior and similar age distribution, the authors determined a shift of 400 former slightly to seriously injured cyclists in Germany per year. Overall this would be an increase of approximately 2.3% in case of 10% of pedelec penetration with the pessimistic assumption of 10 km/h speed increase although first natural driving studies predict a much lower average speed increase of pedelecs. The hypothesis verbalized in the initial question whether a higher distribution of pedelecs will result in more severe accidents in Germany is not verified. The study shows that electrical support didn"t result in higher collision speed in general. In many accident situations, the speed of pedelecs has only a minor influence on the accident severity. Further research focusing on a possible change of driver behavior especially in new target groups (elderly people) will be needed.
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.
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.
The paper aims to study the injury risk and kinematics of pedestrians involved in different passenger vehicle collisions. Furthermore, the difference of pedestrian kinematics in the accidents involved minivan and sedan was analyzed. The 18 sample cases of passenger car to pedestrian collisions were selected from the database of In-depth Investigation of Vehicle Accident in Changsha of China (IVAC),of which the 12 pedestrian accidents involved in a minivan impact for each case, and the 6 accidents in a sedan impact for each. The selected cases were reconstructed by using mathematical models of pedestrians and accident vehicles in a multi-body dynamic code MADYMO environment. The logistic regression models of the risks for pedestrian AIS 3+ injuries and fatalities were developed in terms of vehicle impact speed by analyzing the minivan-pedestrian and sedan-pedestrian accidents. The difference of pedestrian kinematics was identified by comparing the results from reconstructed pedestrian accidents between the minivans and sedans collisions. The result shows that there is a significant correlation among the impact speed and the severity of pedestrian injuries. The minivan poses greater risk to pedestrian than sedan at the same impact speed. The kinematics of pedestrian was greatly influenced by vehicle front shape.
Although the number of road accident casualties in Europe (EU27) is falling the problem still remains substantial. In 2011 there were still over 30,000 road accident fatalities. Approximately half of these were car occupants and about 60 percent of these occurred in frontal impacts. The next stage to improve a car's safety performance in frontal impacts is to improve its compatibility. The objective of the FIMCAR FP7 EU-project was to develop an assessment approach suitable for regulatory application to control a car's frontal impact and compatibility crash performance and perform an associated cost benefit analysis for its implementation. This paper reports the cost benefit analyses performed to estimate the effect of the following potential changes to the frontal impact regulation: • Option 1 " No change and allow current measures to propagate throughout the vehicle fleet. • Option 2 " Add a full width test to the current offset Deformable Barrier (ODB) test. • Option 3 " Add a full width test and replace the current ODB test with a Progressive Deformable Barrier (PDB) test. For the analyses national data were used from Great Britain (STATS 19) and from Germany (German Federal Statistical Office). In addition in-depth real word crash data were used from CCIS (Great Britain) and GIDAS (Germany). To estimate the benefit a generalised linear model, an injury reduction model and a matched pairs modelling approach were applied. The benefits were estimated to be: for Option 1 "No change" about 2.0%; for Option 2 "FW test" ranging from 5 to 12% and for Option 3 "FW and PDB tests" 9 to 14% of car occupant killed and seriously injured casualties.
The number of injured car occupants decreases constantly. Nevertheless, they account for nearly 50% of all fatalities and about 44% of all seriously injured persons in German traffic accidents. Further reductions of casualties require multiple efforts in all parts of traffic safety. In this paper a detailed analysis of the important pre-hospital rescue phase was done. The basis for future improvements is the knowledge about injury causation of car occupants in combination with other corresponding influence factors. For that reason more than 1.200 severe (AIS3+) injuries of frontal car occupants were analyzed. For the most relevant injuries of car occupants multivariate analysis models were created to predict the probability of these injuries in a real crash scenario. In addition to the collision severity different influence factors like impact direction, seat belt usage, age of the occupant, and gender were analyzed. Furthermore, the models were checked regarding the goodness of fit and all results all results were checked concerning their robustness. The prediction models were created on the basis of 5.000 car accidents. Afterwards, the models were validated using 4.000 different car accidents. The prediction of the probability of severe injuries could be used for different applications in the field of traffic safety. One possibility is the implementation of the models in a tool for the on-the-spot diagnosis. The background for the development of such applications is the fact, that there are only limited diagnostic possibilities available at the accident scene. Nevertheless, the rescue forces have to make essential decisions like the alerting of the necessary medical experts, appropriate treatment, the type of transportation and the choice of an adequate hospital. These decisions quite often decide between life and death or influence the long-term effects of injured persons. At this point, indications of expectable injuries could help enormously. To enable even persons with limited technical knowledge to use the tool, a procedure was developed that facilitates the assumption of the given crash severity. Another important possibility for the application of the prediction models is the use for the qualification of information sent by e-call systems.
Because of actual developments and the continuous increase in the field of drive assistant systems, representative and detailed investigations of accident databases are necessary. This lecture describes the possibility to estimate the potential of primary and secondary safety measures by means of a computerized case by case analysis. Single primary or secondary safety measures as well as a combination of both are presented. The method is exemplarily shown for the primary safety measure "Brake Assist" in pedestrian accidents. Regarding accident prevention only the primary safety measure is determined.
At the beginning of the year 2000 the European Commission set the goal to halve the number of road deaths till the year 2010. The main focus are passenger car and lorry traffic. A significant reduction of the accident data could be reached in these groups. The advancement of active vehicle safety systems is an important issue of the programme. The safety of the motorcycle traffic has been disregarded till now. Since 1991 the number of killed motorcycle riders per year has been constant. The number of killed passenger car occupants has been more than halved in the same period. This is why initiatives are caused for the increase of the motorcycle safety. A great safety potential is expected for the Antilock Brake System (ABS). ABS for motorcycles is considered from the economic view in this study. A cost-benefit analysis shall clarify whether the economic benefit of ABS for motorcycles is greater than the consumed resources. Moreover, a sensitivity analysis will determine the maximal justifiable consumption in resource for which ABS is worthwhile. After the sensitivity analysis is done a break-even analysis will determine the market price respectively the annual mileage from which on ABS is worthwhile on user level. For this the fair end consumer market price is calculated which the user is ready to pay. For the considered market prices the annual mileage is determined from which on ABS is worthwhile for the user. The considered time horizon for this analysis are the years 2015 and 2020. For each of these years the accident data is forecasted. At this, it is assumed that the frequency of having an accident per million registered motorcycles decreases based on the present trend. Thus, riding motorcycle gets safer. Hence, the accident data in the years 2015 and 2020 is lower than the accident data today. The cost-benefit analysis is done for each year for four scenarios. Two scenarios handle the market penetration. The first one is the trend scenario, the second one is the mandatory equipment from the year 2010 on. The other scenarios describe the effectiveness of ABS. The effectiveness rates are determined by a literature review. The only potential which can be considered due to the available data is the potential due to an avoiding of the downfall just before the real accident happens. According to this the number of accidents will decrease by 2.4 %. The number of fatalities will decrease by 12.1 %. The number of severe injuries decreases by 11.7 %. However, the number of slight injuries increases by 2.1 %. The mentioned effectiveness rates are valid for the scenarios with the high effectiveness. Even these figures underestimate the actual effectiveness because there are only considered the avoided accidents with downfall. The necessary consumption in resources depends on the produced volume. The more ABS systems are produced, the lower are the costs per system. This is due to realised effects of scale and effects out of learning curves. The system costs depend on the penetration rate. In the trend scenario the system costs for ABS are 120 Euro for the year 2015 respectively 105 Euro for the year 2020. In the mandatory scenario the system costs are 115 Euro for the year 2015 respectively 100 Euro for the year 2020. The benefit-cost ratios are all over the critical barrier of 1.0. Thus, ABS is worthwhile on economic level. In the scenarios with high effectiveness the benefit-cost ratios range between 4.6 and 4.9. Thus, the values are even above the barrier of 3.0. The result of the break-even analysis is that ABS is worthwhile on user level. The considered market prices are 400 Euro in 2015 and 300 Euro in 2020. They are clearly below the determined fair end consumer market prices. The fair end consumer price for the year 2015 is 701 Euro respectively 622 Euro for the year 2020. Thus, ABS is worthwhile for motorcycle riders with an annual mileage higher than 2,200 km (year 2015) respectively 1,900 km (year 2020). The annual mileage of a motorcycle rider is 3,900 km on average. Thus, ABS is worthwhile for most of the motorcycle riders. The mentioned results are valid for the high effectiveness scenarios.