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The road transport infrastructure is facing many challenges and the subsequent adaptation of the infrastructure is of utmost concern. These challenges are as follows: globalization, sustainability, technological and demographic change, an increase in goods transport and climate change. Various climate projections predict changing climatic parameters such as temperature, precipitation and wind speed for Germany. This could have severe impacts on road transport infrastructure as well as road traffic itself. At the Federal Highway Research Institute (Bundesanstalt für Straßenwesen), a strategy was developed to adapt roads and engineering structures to the impacts of climate change. The strategy "Anpassung der Straßenverkehrsinfrastruktur an den Klimawandel /Adaptation of road traffic infrastructure to climate change (AdSVIS)" currently comprises about 15 projects. Adaptation measures are to be developed for the identified risk areas and consequently their effectiveness has to be assessed.
Research to inform policy is often challenged with how to genuinely use and implement research findings in decision-making and policy-planning. To begin with, the dialogue between researchers and decision-makers is essential to ensure profound understanding and legitimate interpretations of the results. Furthermore, the step to drawing practical conclusions and processing them into actions can only succeed if research findings are diffused to decision-making levels with influence on the matter, and mechanisms to knowledge transfer in the presence of a stable, favourable policy environment exist. Research investments into the topic of electromobility in Europe are substantial, and subtopics aiming to inform national policy-makers address a complex set of aspects from environmental and societal to technological and economic. This paper has a two-fold objective, the first of which is to present the results of scenarios to explore electromobility deployment in Finland, Germany and the European Union. The second is to discuss the challenges and solutions to bridge the gap from research findings towards decision-making and policy-planning, using the authors' electromobility scenario work as an example. The electromobility scenarios were built using the VECTOR21 model (Mock, 2010), and the rationale was to simulate vehicle sales and markets under different policy settings and calculate the most economical solution to fulfill regulation on COâ‚‚ emissions as set by the European Commission (2009). The model allows calculating the market diffusion of alternative powertrain technologies to the European market until 2030, taking into account different taxation schemes, incentives and other country-specific characteristics. The authors also present the cost-benefit-analysis of the modelling results to assess the different scenarios and to show variation between regions regarding profitability of alternative technological or political support and interventions. To proceed from research findings towards decision-making and policy-planning, the authors made observations relating to transfer of research knowledge and interpretation of their electromobility scenario results in national policy contexts. An evaluation of how the function of research to inform policy in this case succeeded is provided. In addition, the influence of expert opinions on the political decision-making process will be discussed through experiences from an expert questionnaire conducted to survey the importance of costs, time requirement, acceptance and other criteria of promotion measures of electromobility.
Fire incidents are among the most relevant for people in a tunnel. Therefore, it is important to be sufficiently prepared for such events. A large scale fire test is to be used to help evaluate the initial burning duration and the time it takes for the fire to spread to other vehicles in the tunnel, and in particular how long it takes for a truck carrying wooden pallets to catch fire, taking into consideration the extremely high temperatures. The goal, therefore, is to determine the time it takes for a fire to spread to other vehicles in the tunnel. In the large scale fire test, an accident in a tunnel with one-way traffic is simulated between a truck loaded with approximately 3.7 t of wooden Europol pallets and a passenger car. Directly behind each of the vehicles involved in the accident there is another car which stops at a distance of 1.0 m. Approximately 300 litres of burning diesel are discharged from the truck's fuel tank, which is simulated by using approximately 400 litres of isopropanol. A 10 m-² burning pool forms underneath the truck. Other objectives of the large scale fire test are the validation of the CFD models and the evaluation of the progression of the thermal release ratios estimated for the simulation. The thermal release ratios generated in the test are determined and evaluated using various models.
Motorcycling is a fascinating kind of transportation. While the riders' direct exposure to the environment and the unique driving dynamics are essential to this fascination, they both cause a risk potential which is several times higher than when driving a car. This chapter gives a detailed introduction to the fundamentals of motorcycle dynamics and shows how its peculiarities and limitations place high demands on the layout of dynamics control systems, especially when cornering. The basic principles of dynamic stabilization and directional control are addressed along with four characteristic modes of instability (capsize, wobble, weave, and kickback). Special attention is given to the challenges of braking (brake force distribution, dynamic over-braking, kinematic instability, and brake steer torque induced righting behavior). It is explained how these challenges are addressed by state-of-the-art brake, traction, and suspension control systems in terms of system layout and principles of function. It is illustrated how the integration of additional sensors " essentially roll angle assessment " enhances the cornering performance in all three categories, fostering a trend to higher system integration levels. An outlook on potential future control systems shows exemplarily how the undesired righting behavior when braking in curves can be controlled, e.g., by means of a so-called brake steer torque avoidance mechanism (BSTAM), forming the basis for predictive brake assist (PBA) or even autonomous emergency braking (AEB). Finally, the very limited potential of brake and chassis control to stabilize yaw and roll motion during unbraked cornering accidents is regarded, closing with a promising glance at roll stabilization through a pair of gimbaled gyroscopes.
In line with the new definition introduced by the European Commission (EC), the number of seriously injured road casualties in Germany for 2014 is assessed in this study. The number of MAIS3+ casualties is estimated by two different methodological approaches. The first approach is based on data from the German Inâ€Depth Accident Study (GIDAS), which is closely related to the German Road Traffic Accident Statistics. The second approach is based on data from the German TraumaRegister DGU-® (TRâ€DGU), which includes many more hospitals but not all MAIS3+ injuries.
Automated driving will provide many kinds of benefits - some direct and some indirect. The benefits originate at the individual level, from changes in the behaviour of drivers and travellers with regard to driving and mobility, ending up with benefits at the social level via changes in the whole transport system and society, where many of the current planning and operations paradigms are likely to be transformed by automated driving. There may also be disbenefits, particularly at a social level, for example in intensity of travel which could result in additional congestion and increased use of natural resources. There may also be unintended consequences. For example, we do not know the impacts on public transport: driverless vehicles could provide a means to a lower cost service provision, but the availability of automated cars could lead to more car travel at the expense of collective transport.
Risk-based approach for the protection of land transport infrastructure against extreme rainfall
(2016)
The aim of the research project "Risk based approach for the protection of transport infrastructure against extreme rainfall RAINEX" is the development of a practical methodology for the identification and assessment of both vulnerable as well as critical transport infrastructures towards extreme rainfall events consequences. The developed methodology is based on expert knowledge and includes qualitative and semi-quantitative analyses regarding the assessment of the vulnerability and criticality of relevant transport infrastructures. The process chain from the spatial rainfall to the concentrated runoff in the river channel was shown to assess the local hazard resulting in the local risk. The main result of the project is a practice-oriented and applicable methodology and a comprehensive and well-developed security handbook.
Urban runoff is known to transport a significant pollutant load consisting of e.g. heavy metals, salts and hydrocarbons. Interactions between solid and dissolved compounds, proper understanding of particle size distribution, dissolved pollutant fractions and seasonal variations is crucial for the selection and development of appropriate road runoff treatment devices. Road runoff at an arterial road in Augsburg, Germany, has been studied for 3.5 years. A strong seasonal variation was observed, with increased heavy metal concentrations with doubled and tripled median concentrations for heavy metals during the cold season. Correlation analysis showed that de-icing salt is not the only factor responsible for increased pollutant concentrations in winter. During the cold period, the fraction of dissolved metals was lower compared to the warm season. In road dust, the highest metal concentrations were measured for fine particles. Metals in road runoff were found to show a significant correlation to fine particles SS63 (<63 μm). Therefore, it is debatable whether treatment devices only implementing sedimentation processes provide sufficient removal rates.
Measuring and characterizing airborne particulate matter (PM) is an important research area because PM can lead to impacts on health and to visibility reduction, material damage and groundwater pollution. In regard to road dust, suspension and re-suspension and the contribution of non-exhaust PM to total traffic emissions are expected to increase as a result of predicted climate scenarios. European environmental regulations have been enforced to reduce exhaust particle emissions from road traffic, but little attention has been paid to reducing non-exhaust coarse particle emissions due to traffic. Therefore, a monitoring program for coarse PM has been initiated in early 2013 to assess the predicted increase in the abundance of non-exhaust particles. Particle sampling was performed with the passive-sampler technique Sigma-2. The subsequent single-particle analysis allows for characterization of individual particles, determination of PM size distribution, and calculation of PM mass concentrations. Two motorways n ear Cologne (Koeln), Germany were selected as sampling sites, and the experimental setup in the field was realized with a so-called twin-site method. The present study reports single-particle analysis data for samples collected between May 31, 2013 and May 30, 2014. Coarse PM, generated through multi-source mechanisms, consists of, e.g., tire-wear, soot aggregates, and mineral dust. The highest mass concentration occurs at both motorways in spring, and the observed PM mainly contains traffic-abrasion particles. The field measurements show that the minimum PM concentration was found in the 5 to 12-°C temperature range, whereas the maximum concentration was observed in both the "5 to 5-°C and the 12 to 24-°C ranges, in agreement with previous laboratory measurements. Correlation between super-coarse (d p 10"80 μm, geometric equivalent diameter) PM concentration and precipitation displays a significant increase in concentration with decreasing number of precipitation events (dry weather periods).
Chronic non-cancer pain (CNCP) is a major health problem. Patients are increasingly treated with chronic opioid therapy (COT). Several laboratory studies have demonstrated that long-term use of opioids does not generally impair driving related skills. But there is still a lack of studies investigating on-the-road driving performance in actual traffic. The present study assessed the impact of COT on road-tracking and car-following performance in CNCP patients. Twenty CNCP patients, long-term treated with stable doses of opioid analgesics, and 19 healthy controls conducted standardized on-the-road driving tests in normal traffic. Performance of controls with a blood alcohol concentration (BAC) of 0.5 g/L was used as a reference to define clinically relevant changes in driving performance. Standard Deviation of Lateral Position (SDLP), a measure of road-tracking control, was 2.57 cm greater in CNCP patients than in sober controls. This difference failed to reach statistical significance in a superiority test. Equivalence testing indicated that the 95% CI around the mean SDLP change was equivalent to the SDLP change seen in controls with a BAC of 0.5 g/L and did not include zero. When corrected for age differences between groups the 95% CI widened to include both the alcohol reference criterion and zero. No difference was found in car-following performance. Driving performance of CNCP patients did not significantly differ from that of controls due to large inter-individual variations. Hence in clinical practice determination of fitness to drive of CNCP patients who receive opioid treatments should be based on an individual assessment.