The Zero Lower Bound on nominal interest rates and its impact on monetary policy in the “New Normal”

This dissertation aims to illustrate the impact of the Zero Lower Bound (ZLB) on nominal interest rates, based on a deterministic simulation of Fernández-Villaverde and Rubio-Ramírez’ (2006) DSGE model of the U.S. economy. I calibrate the model for 2 different steady states, the first based on historical data (old steady state) and the second matching the most recent data, with lower inflation and lower real interest rates (new steady state). Within these calibrations I simulate the impact of a set of representative shocks. The ZLB appears to be of minor relevance in the old steady state while it is found to be a significant constraint in the new steady state. The associated impact on activity is relatively small but not negligible. My results are robust assuming alternative monetary policy rules. Hence, I conclude that conventional monetary policy tools are insufficient to anticipate the increased risk of hitting the ZLB in the new steady state. Further analysis of the exact transmission mechanism is warranted due to the simplified assumptions underlying this dissertation.Esta dissertação pretende ilustrar o impacto do limiar inferior das taxas de juros nominais (ZLB), com base numa simulação determinística do modelo DSGE para os EUA apresentado em Fernández-Villaverde e Rubio-Ramírez (2006). O modelo é calibrado para 2 estados estacionários, o primeiro com base em dados históricos (antigo estado estacionário) e o segundo com base em dados recentes, caracterizados por uma menor inflação e taxas de juros reais mais baixas (novo estado estacionário). Com base nesta calibrações, é simulado o impacto de um conjunto de choques representativos. O ZLB parece ser de menor relevância no antigo estado estacionário enquanto se verifica ser uma restrição significativa no novo estado estacionário. O impacto associado na atividade é relativamente pequeno, mas não negligenciável. Os resultados são robustos a regras de política monetária alternativas. Assim, concluo que os instrumentos convencionais de política monetária são insuficientes para evitar o maior risco de atingir o ZLB no novo estado estacionário. Mais investigação sobre o mecanismo de transmissão monetária próximo do ZLB é necessário, dadas as hipóteses simplificadoras subjacentes a esta dissertação

Der Einfluss von Entspannungsverfahren auf die willentliche Aktivierung der absteigenden Schmerzhemmung

Chronische Schmerzen führen zu einer starken individuellen und gesellschaftlichen Belastung und haben mit 13 - 31 % weltweit eine hohe Prävalenz. Die Weltgesundheitsorganisation zählt ihre Behandlung zu den größten medizinischen Herausforderungen unserer Zeit. Ein vielversprechender nicht medikamentöser Therapieansatz ist das von Ruscheweyh et al. 2015 gezeigte Erlernen der willentlichen Beeinflussung der spinalen nozizeptiven Transmission unter visuellem Feedback des nozizeptiven Flexorreflexes (NFR). Nach Hinweisen auf positive Effekte bei gleichzeitiger Anwendung von Entspannungsverfahren wurden in der vorliegenden Studie die Auswirkungen der progressiven Muskelrelaxation (PMR) auf das Erlernen dieser Methode untersucht. Weitere Ziele waren die Beständigkeit des Trainingserfolgs, die Übertragbarkeit auf eine Situation ohne Feedback und mögliche Einflüsse auf die spinalen Motorik zu überprüfen. Dazu erlernten gesunde Probanden (n = 45) an drei Trainingsterminen ihre spinale nozizeptive Transmission zu beeinflussen. Eine Versuchsgruppe (FBE-Gruppe, n = 15) erlernte vor dem Training die PMR und trainierte anschließend mit Feedback des NFR, eine weitere (FB-Gruppe, n = 15) trainierte nur mit NFR-Feedback und eine Kontrollgruppe (KO-Gruppe, n = 15) trainierte ohne NFR-Feedback und ohne das Erlernen der PMR. Nach drei und neun Monaten wurde nach erfolgreichem Training die Beständigkeit des Trainingserfolgs und die Übertragbarkeit auf eine Situation ohne Feedback überprüft. Der Trainingserfolg in der FBE-Gruppe war dem in der KO-Gruppe signifikant überlegen, nicht jedoch dem in der FB-Gruppe. In der FBE-Gruppe war ein signifikanter Trainingseffekt zwischen den Terminen nachweisbar und 80 % der Probanden aus dieser Gruppe erreichten eine NFR-Reduktion auf < 80 % des Ausgangswerts (NNT 1,5). Der Trainingserfolg war nach drei und neun Monaten vollständig erhalten und ein erfolgreicher Transfer auf eine Situation ohne Feedback möglich. Eine Veränderung der Erregbarkeit spinaler Motoneurone konnte nicht nachgewiesen werden. Die vorliegenden Ergebnisse erweitern das Grundlagenwissen zur Beeinflussung der spinalen nozizeptiven Transmission und tragen als experimentelleGrundlage fur weitere Studien mit chronischen Schmerzpatienten bei, um die Möglichkeit des klinischen Einsatzes dieser Methode in der Schmerztherapie zu untersuchen

Learning from Covid: How Can we Predict Mobility Behaviour in the Face of Disruptive Events? – How to Investigate the Mobility of the Future

Introduction: With the beginning of the COVID-19 outbreak and the restrictions put in place to prevent an uncontrolled spread of the virus, the circumstances for daily activities changed. A remarkable shift in the modal split distribution was observed [Ank21]. Moreover, the changes in mobility during the COVID-19 pandemic had multiple impacts on road traffic [Yas21]. By now, several researchers have looked at the impact of COVID-19 as a disruptive event on mobility behaviour. This workshop within the 4th Symposium on Management of Future Motorway and Urban Traffic Systems aimed to discuss insights from these research projects and how they enable experts to transfer this newfound knowledge to future disruptive events such as climate change, rising energy costs and events related to a possible energy transition. Thus, the research question this workshop investigated reads as follows: What can we learn from the pandemic to be able to predict how different future disruptive events can shape the mobility of tomorrow

Necessity of Immediate MRI Imaging in the Acute Care of Severely Injured Patients

Background and Objectives: The standard diagnostic procedure for a patient with a suspected polytrauma injury is computed tomography (CT). In individual cases, however, extended acute imaging using magnetic resonance imaging (MRI) can provide valuable and therapy-relevant information. The aim of our cohort study was to find such cases and to describe their characteristics in order to be able to give possible recommendations for MRI application in acute trauma situations. Materials and Methods: In the study period from 2015–2019, an evaluation of the imaging performed on polytrauma patients was carried out. The specific diagnostic and therapeutic criteria of the MRI group were further defined. Results: In total, 580 patients with an ISS ≥16 (injury severity score) were included in the study. Of these 580 patients, 568 patients received a CT scan and 12 patients an MRI scan as part of the initial diagnostic. Altogether, 66.67% of the MRIs took place outside of regular service hours. The main findings for MRI indications were neurological abnormalities with a focus on myelon injuries. Further MRI examinations were performed to rule out vascular injuries. All in all, 58.3% of the MRIs performed resulted in modified therapeutic strategies afterward. Conclusions: MRI in the context of acute diagnostic of a severely injured patient will likely remain reserved for special indications in the future. However, maximum care hospitals with a high flow of severely injured patients should provide 24/7 MR imaging to ensure the best possible care, especially in neurological and blunt vascular injuries

Towards Safer Rides: Measuring Motorcycle Dynamics with Smartphones

Motorradfahrer gehören zu den am meisten gefährdeten Verkehrsteilnehmern im Straßenverkehr. Häufig ist die Unfallursache ein Kontrollverlust auf Landstraßen, der durch Ausnutzung des physikalischen Potenzials in Form von größeren Schräglagenwinkeln vermieden werden könnte. Gleichzeitig sind in der Realität gefahrene Schräglagen über eine größere Gruppe von Fahrern und eine längere Strecke unbekannt, was vor allem auf die erforderliche spezielle Messtechnik zurückzuführen ist. Der Schwerpunkt liegt daher auf der Entwicklung eines kostengünstigen Messverfahrens zur Messung der Schräglagenwinkel von Motorrädern. Smartphones zeichnen sich in der Regel durch integrierte Inertialsensoren aus, die für die Erfassung der Fahrdynamik von Motorrädern geeignet sind. Mit Hilfe einer auf die Anforderungen zugeschnittenen Smartphone-App zur Erfassung von Messdaten auf dem Motorrad werden die Daten der Sensoren aufgezeichnet. Anschließend werden mittels einer Offline-Auswertung die Drehwinkel zwischen dem Smartphone und dem Motorrad-Koordinatensystem bestimmt, die inertialen Messdaten transformiert und der Schräglagenwinkel berechnet. Ein wesentlicher Bestandteil ist die Validierung der entwickelten Messkette durch einen Vergleich der Ergebnisse mit einem hochpräzisen Messsystem. Dieser wurde auf verschiedenen Strecken zur Bestimmung der Datenqualität durchgeführt. Als Machbarkeitsstudie diente eine Probandenstudie, die die Praxistauglichkeit der Messkette bestätigte. Die Studienergebnisse werden zusätzlich auszugsweise dargestellt und diskutiert. Die erfolgreiche Validierung auf verschiedenen Strecken, die Praxistauglichkeit der Datenerfassung und die Genauigkeit des Messsystems ermutigen dazu, die Smartphone-App auf ein größeres Panel von Testpersonen auszurollen und damit Daten über ein größeres Fahrerkollektiv zu erheben.:Introduction, State of Research, Methods, Measurement Chain Verification, Results and Discussion, ConclusionMotorcyclists are among the most vulnerable road users in road traffic. Often, the cause of accidents is a loss of control on rural roads which could be averted by making use of the physical potential in terms of larger lean angles. At the same time, in reality driven lean angles over a larger group of riders and a longer route are unknown which is mainly due to the special measuring technology required. The focus is therefore on the development of a low-cost measurement method for measuring the lean angles of motorcycles. Smartphones are usually characterized by integrated inertial sensors, which are suitable for the acquisition of motorcycle driving dynamics. Employing a smartphone app tailored to the requirements for collecting measurement data on the motorcycle, the data of the sensors are recorded. During the offline evaluation, the rotation angles between the smartphone and the motorcycle coordinate system are determined, the inertial measurement data are transformed and the roll angle is calculated. An essential part is the alignment of the developed measurement chain with a high-precision measurement system. This was carried out on different routes and thus the data quality was determined. As a feasibility study, a test person study with several participants was carried out, which confirmed the practical suitability of the measurement chain. Hence, the study outcomes are briefly shown and discussed. The successful validation on different routes, the practical suitability of the data acquisition and the accuracy of the measurement system encourage to roll out the smartphone app to a larger panel of test persons and thus to collect data on a larger driver collective.:Introduction, State of Research, Methods, Measurement Chain Verification, Results and Discussion, Conclusio

Towards Safer Rides: Measuring Motorcycle Dynamics with Smartphones

Motorradfahrer gehören zu den am meisten gefährdeten Verkehrsteilnehmern im Straßenverkehr. Häufig ist die Unfallursache ein Kontrollverlust auf Landstraßen, der durch Ausnutzung des physikalischen Potenzials in Form von größeren Schräglagenwinkeln vermieden werden könnte. Gleichzeitig sind in der Realität gefahrene Schräglagen über eine größere Gruppe von Fahrern und eine längere Strecke unbekannt, was vor allem auf die erforderliche spezielle Messtechnik zurückzuführen ist. Der Schwerpunkt liegt daher auf der Entwicklung eines kostengünstigen Messverfahrens zur Messung der Schräglagenwinkel von Motorrädern. Smartphones zeichnen sich in der Regel durch integrierte Inertialsensoren aus, die für die Erfassung der Fahrdynamik von Motorrädern geeignet sind. Mit Hilfe einer auf die Anforderungen zugeschnittenen Smartphone-App zur Erfassung von Messdaten auf dem Motorrad werden die Daten der Sensoren aufgezeichnet. Anschließend werden mittels einer Offline-Auswertung die Drehwinkel zwischen dem Smartphone und dem Motorrad-Koordinatensystem bestimmt, die inertialen Messdaten transformiert und der Schräglagenwinkel berechnet. Ein wesentlicher Bestandteil ist die Validierung der entwickelten Messkette durch einen Vergleich der Ergebnisse mit einem hochpräzisen Messsystem. Dieser wurde auf verschiedenen Strecken zur Bestimmung der Datenqualität durchgeführt. Als Machbarkeitsstudie diente eine Probandenstudie, die die Praxistauglichkeit der Messkette bestätigte. Die Studienergebnisse werden zusätzlich auszugsweise dargestellt und diskutiert. Die erfolgreiche Validierung auf verschiedenen Strecken, die Praxistauglichkeit der Datenerfassung und die Genauigkeit des Messsystems ermutigen dazu, die Smartphone-App auf ein größeres Panel von Testpersonen auszurollen und damit Daten über ein größeres Fahrerkollektiv zu erheben.:Introduction, State of Research, Methods, Measurement Chain Verification, Results and Discussion, ConclusionMotorcyclists are among the most vulnerable road users in road traffic. Often, the cause of accidents is a loss of control on rural roads which could be averted by making use of the physical potential in terms of larger lean angles. At the same time, in reality driven lean angles over a larger group of riders and a longer route are unknown which is mainly due to the special measuring technology required. The focus is therefore on the development of a low-cost measurement method for measuring the lean angles of motorcycles. Smartphones are usually characterized by integrated inertial sensors, which are suitable for the acquisition of motorcycle driving dynamics. Employing a smartphone app tailored to the requirements for collecting measurement data on the motorcycle, the data of the sensors are recorded. During the offline evaluation, the rotation angles between the smartphone and the motorcycle coordinate system are determined, the inertial measurement data are transformed and the roll angle is calculated. An essential part is the alignment of the developed measurement chain with a high-precision measurement system. This was carried out on different routes and thus the data quality was determined. As a feasibility study, a test person study with several participants was carried out, which confirmed the practical suitability of the measurement chain. Hence, the study outcomes are briefly shown and discussed. The successful validation on different routes, the practical suitability of the data acquisition and the accuracy of the measurement system encourage to roll out the smartphone app to a larger panel of test persons and thus to collect data on a larger driver collective.:Introduction, State of Research, Methods, Measurement Chain Verification, Results and Discussion, Conclusio

Towards Safer Rides: Measuring Motorcycle Dynamics with Smartphones

Motorradfahrer gehören zu den am meisten gefährdeten Verkehrsteilnehmern im Straßenverkehr. Häufig ist die Unfallursache ein Kontrollverlust auf Landstraßen, der durch Ausnutzung des physikalischen Potenzials in Form von größeren Schräglagenwinkeln vermieden werden könnte. Gleichzeitig sind in der Realität gefahrene Schräglagen über eine größere Gruppe von Fahrern und eine längere Strecke unbekannt, was vor allem auf die erforderliche spezielle Messtechnik zurückzuführen ist. Der Schwerpunkt liegt daher auf der Entwicklung eines kostengünstigen Messverfahrens zur Messung der Schräglagenwinkel von Motorrädern. Smartphones zeichnen sich in der Regel durch integrierte Inertialsensoren aus, die für die Erfassung der Fahrdynamik von Motorrädern geeignet sind. Mit Hilfe einer auf die Anforderungen zugeschnittenen Smartphone-App zur Erfassung von Messdaten auf dem Motorrad werden die Daten der Sensoren aufgezeichnet. Anschließend werden mittels einer Offline-Auswertung die Drehwinkel zwischen dem Smartphone und dem Motorrad-Koordinatensystem bestimmt, die inertialen Messdaten transformiert und der Schräglagenwinkel berechnet. Ein wesentlicher Bestandteil ist die Validierung der entwickelten Messkette durch einen Vergleich der Ergebnisse mit einem hochpräzisen Messsystem. Dieser wurde auf verschiedenen Strecken zur Bestimmung der Datenqualität durchgeführt. Als Machbarkeitsstudie diente eine Probandenstudie, die die Praxistauglichkeit der Messkette bestätigte. Die Studienergebnisse werden zusätzlich auszugsweise dargestellt und diskutiert. Die erfolgreiche Validierung auf verschiedenen Strecken, die Praxistauglichkeit der Datenerfassung und die Genauigkeit des Messsystems ermutigen dazu, die Smartphone-App auf ein größeres Panel von Testpersonen auszurollen und damit Daten über ein größeres Fahrerkollektiv zu erheben.:Introduction, State of Research, Methods, Measurement Chain Verification, Results and Discussion, ConclusionMotorcyclists are among the most vulnerable road users in road traffic. Often, the cause of accidents is a loss of control on rural roads which could be averted by making use of the physical potential in terms of larger lean angles. At the same time, in reality driven lean angles over a larger group of riders and a longer route are unknown which is mainly due to the special measuring technology required. The focus is therefore on the development of a low-cost measurement method for measuring the lean angles of motorcycles. Smartphones are usually characterized by integrated inertial sensors, which are suitable for the acquisition of motorcycle driving dynamics. Employing a smartphone app tailored to the requirements for collecting measurement data on the motorcycle, the data of the sensors are recorded. During the offline evaluation, the rotation angles between the smartphone and the motorcycle coordinate system are determined, the inertial measurement data are transformed and the roll angle is calculated. An essential part is the alignment of the developed measurement chain with a high-precision measurement system. This was carried out on different routes and thus the data quality was determined. As a feasibility study, a test person study with several participants was carried out, which confirmed the practical suitability of the measurement chain. Hence, the study outcomes are briefly shown and discussed. The successful validation on different routes, the practical suitability of the data acquisition and the accuracy of the measurement system encourage to roll out the smartphone app to a larger panel of test persons and thus to collect data on a larger driver collective.:Introduction, State of Research, Methods, Measurement Chain Verification, Results and Discussion, Conclusio

Validating automated driving systems by using scenario-based testing: The Fuse4Rep process model for scenario generation as part of the 'Dresden Method

Scenario-based testing emerges as the main approach to validate automated driving systems (ADS) and thus ensure safe road traffic. Thereby, the test scenarios used should represent the traffic event of the corresponding operational design domain (ODD) and should cover the traffic situation from normal driving to an accident. For this, the fusion of police accident data and video-based traffic observation data into one database for subsequent scenario generation is advisable. Therefore, this paper presents the Fuse4Representativity (Fuse4Rep) process model as part of the Dresden Method, which helps to fuse heterogeneous data sets into one ODD-representative database for lean, fast and comprehensive scenario generation. Hereby, statistical matching is used as the fusion approach building on probable matching variables, such as the 3-digit accident type, the collision type and the misconduct of participants. Moreover, the paper shows how the scenarios generated in this way can be hypothetically used to validate ADS, e.g. in a stochastic traffic simulation incorporating human driver behaviour models. Future studies should apply the Fuse4Rep model in practice and test its validity

Validating automated driving systems by using scenario-based testing: The Fuse4Rep process model for scenario generation as part of the 'Dresden Method

Scenario-based testing emerges as the main approach to validate automated driving systems (ADS) and thus ensure safe road traffic. Thereby, the test scenarios used should represent the traffic event of the corresponding operational design domain (ODD) and should cover the traffic situation from normal driving to an accident. For this, the fusion of police accident data and video-based traffic observation data into one database for subsequent scenario generation is advisable. Therefore, this paper presents the Fuse4Representativity (Fuse4Rep) process model as part of the Dresden Method, which helps to fuse heterogeneous data sets into one ODD-representative database for lean, fast and comprehensive scenario generation. Hereby, statistical matching is used as the fusion approach building on probable matching variables, such as the 3-digit accident type, the collision type and the misconduct of participants. Moreover, the paper shows how the scenarios generated in this way can be hypothetically used to validate ADS, e.g. in a stochastic traffic simulation incorporating human driver behaviour models. Future studies should apply the Fuse4Rep model in practice and test its validity

Generating representative test scenarios: The FUSE for Representativity (fuse4rep) process model for collecting and analysing traffic observation data

Scenario-based testing is a pillar of assessing the effectiveness of automated driving systems (ADSs). For data-driven scenario-based testing, representative traffic scenarios need to describe real road traffic situations in compressed form and, as such, cover normal driving along with critical and accident situations originating from different data sources. Nevertheless, in the choice of data sources, a conflict often arises between sample quality and depth of information. Police accident data (PD) covering accident situations, for example, represent a full survey and thus have high sample quality but low depth of information. However, for local video-based traffic observation (VO) data using drones and covering normal driving and critical situations, the opposite is true. Only the fusion of both sources of data using statistical matching can yield a representative, meaningful database able to generate representative test scenarios. For successful fusion, which requires as many relevant, shared features in both data sources as possible, the following question arises: How can VO data be collected by drones and analysed to create the maximum number of relevant, shared features with PD? To answer that question, we used the Find–Unify–Synthesise–Evaluation (FUSE) for Representativity (FUSE4Rep) process model.We applied the first (“Find”) and second (“Unify”) step of this model to VO data and conducted drone-based VOs at two intersections in Dresden, Germany, to verify our results. We observed a three-way and a four-way intersection, both without traffic signals, for more than 27 h, following a fixed sample plan. To generate as many relevant information as possible, the drone pilots collected 122 variables for each observation (which we published in the ListDB Codebook) and the behavioural errors of road users, among other information. Next, we analysed the videos for traffic conflicts, which we classified according to the German accident type catalogue and matched with complementary information collected by the drone pilots. Last, we assessed the crash risk for the detected traffic conflicts using generalised extreme value (GEV) modelling. For example, accident type 211 was predicted as happening 1.3 times per year at the observed four-way intersection. The process ultimately facilitated the preparation of VO data for fusion with PD. The orientation towards traffic conflicts, the matched behavioural errors and the estimated GEV allowed creating accident-relevant scenarios. Thus, the model applied to VO data marks an important step towards realising a representative test scenario database and, in turn, safe ADSs