This master’s thesis is dedicated to Side Impact Crash Tests Measurement in company Skoda Auto a.s.. Thesis describes measuring chain devices of Crash Test Laboratory, and also transferring and assessment process of crash record. Main part of Thesis describes eligible acceleration transducer attachment to B-Pillar of a vehicle.

The main subject of this master thesis is the computational modeling of stress-strain analysis of the loaded front part of Toyota Yaris from the year 2010 using an explicit finite element method (FEM). The aim of this thesis is the assessment of resistance of the front part of the car (longeron) at the impact stress. This thesis describes the selection, editing, and creation of the computational model of longeron and simulation of the barrier collision. The objective of the thesis is to use a real vehicle, suggest modified longerons to be implemented in it, test various shape and material versions of the longeron and make their comparison.

This thesis presents four crash test of two cars, in which always a moving vehicle strikes with fully overlaid front part into the side part (cabin for passengers) of another stationary vehicle. Crash test were carried out to detect the impact parameters for use in the road accidents analysis. Experimentally measured data and the acquisition of documentation during crash tests were therefore analyzed in an appropriate manner in order to obtain relevant impact parameters. One of the main evaluated parameters was the deformation energy that has been used for the permanent damage to vehicles. In the forensic engineering practice for analyzing vehicle impacts is as a control parameter used EES (Energy Equivalent Speed), this parameter was counted according to measured values during crash tests.

L’aorte est une artère majeure et la rupture de l’aorte (RA) est la lésion la plus commune parmi les larges vaisseaux. Une RA est détectée dans 10 à 15% des cas mortels liés aux accidents de voiture et constitue la cause secondaire des morts consécutives aux chocs traumatiques associés à ces accidents. Les mécanismes variés de RA (éclatement soudain de l’aorte, la contrainte des structures osseuses, le « coup de bélier » et la combinaison de ces mécanismes) peuvent être considérés comme une combinaison de deux types de contributions : la distraction aortique et la pression aortique.L’objectif de ce travail de doctorat est d’étudier les mécanismes liés aux RAs dans les accidents de voitures en se focalisant sur les mécanismes associés à la pression intra-aortique. Le travail est organisé en quatre parties : 1) quantifier la réponse aortique sous des conditions de chargement physiologiques, 2) identifier la nécessité de considérer la pression intra-aortique dans les RA associés aux accidents, 3) développer un modèle d’éléments finis incluant la contribution des mécanisme de lésions et 4) et finalement étudier le mécanisme de RA avec le modèle nouvellement développé. / Blunt aortic rupture (BAR) is the second leading cause of death following blunt trauma in motor vehicle crash accidents (MVCAs). Aortic distraction was postulated to be a primary BAR mechanism, but intra-aortic pressure effect on BAR is controversial. Previous finite element (FE) simulations did not simultaneously study the BAR mechanisms of the two contribution sources. Therefore, the BAR mechanisms remain to be ascertained under the effects of physiological intra-aortic pressure and intra-thoracic interactions during MVCAs.Our objective is to investigate BAR mechanisms in MVCAs with a focus on intra-aortic pressure. The work is organized: 1) to quantify aortic responses under cardiac function, 2) to identify the necessity of considering intra-aortic pressure, 3) to develop a FE model including both injury contribution sources and 4) to investigate BAR mechanism during MVCA with the new model. The aortic responses under cardiac loadings should be considered for BAR. Intra-aortic pressure could induce a significant BAR risk. BAR in MVCA resulted from a combined mechanism with aortic stretch and intra-aortic pressure as the primary and secondary cause.

<p>Ninety-five percent of all roadway crashes are attributed fully or partially to human error, and a multitude of safety-related programs, policies, and initiatives have seen limited success in reducing roadway crashes and their accompanying fatalities, injuries, and property damage. For this reason, safety professionals have lauded the emergence of autonomous vehicles (AVs) as a promising palliative to the persistent problem of road crashes. Such optimism is reflected in recent literature that have argues from a conceptual standpoint, that road safety enhancement will be one of the prospective benefits of AV operations because automation removes humans from vehicle driving operations and therefore criminates or mitigates human error. It can be argued that the safety benefits of AVs will be manifest when AV market penetration reaches 100%. However, it seems clear from a practical standpoint that the transition from a system of exclusively human-driven vehicles (HDVs) to that of exclusively AVs will not only be necessary but also an arduous journey. This transition period will be characterized by heterogeneous traffic, where human-driven vehicles (HDVs) and AVs share the road space, and whence the prospective safety benefits of AVs may not be fully realized due to human error arising from the HDV operations in the mixed traffic space. These traffic conflicts, which may lead to collisions, could arise from any of several contexts of driving maneuvers, one of which is aggressive lane changes, the focus of this thesis. From the literature, it is clear that lane changing is inherently more collision-prone compared to most other maneuvers including car following, and therefore the consequences of errant human driving behavior such as inattention of misjudgment during lane changing, are more severe. To address this problem, this thesis developed a control framework to be used by AVs to help them avoid collision in a mixed traffic stream with human drivers who exhibit aggressive lane-changing behavior. The developed framework, which is based on a Model Predictive Control (MPC) approach, is designed to control the AV’s movements safely by duly accommodating potential human error from the HDVs that could otherwise lead to any of two common collision patterns: rear-end and side-impact. Further, the thesis investigated how connectivity between the HDVs, and AVs could facilitate joint operational decision-making and sharing of real-time information, thereby further enhancing the safety of the entire traffic stream. Finally, the thesis presents the results of driving simulations carried out to test and validate the performance of the control framework under different traffic conditions.</p>

Objective: State-of-the-art collision avoidance and collision mitigation systems predict the behavior of pedestrians based on trivial models that assume a constant acceleration or velocity. New sources of sensor information—for example, smart devices such as smartphones, tablets, smartwatches, etc.—can support enhanced pedestrian behavior models. The objective of this article is the development and implementation of a V2Xpedestrian collision avoidance system that uses new information sources. Methods: A literature review of existing state-of-the-art pedestrian collision avoidance systems, pedestrian behavior models in advanced driver assistance systems (ADAS), and traffic simulations is conducted together with an analysis of existing studies on typical pedestrian patterns in traffic. Based on this analysis, possible parameters for predicting pedestrian behavior were investigated. The results led to new requirements from which a concept was developed and implemented. Results: The analysis of typical pedestrian behavior patterns in traffic situations showed the complexity of predicting pedestrian behavior. Requirements for an improved behavior prediction were derived. A concept for a V2X collision avoidance system, based on a cost function that predicts pedestrian near future presence, and its implementation is presented. The concept presented considers several challenges such as information privacy, inaccuracies of the localization, and inaccuracies of the prediction. Conclusion: A concept for an enhanced V2X pedestrian collision avoidance system was developed and introduced. The concept uses new information sources such as smart devices to improve the prediction of the pedestrian's presence in the near future and considers challenges that come along with the usage of these information sources.

This research focuses on the Crash Analysis Methodology for Segments (CAMS) which provides a way for engineers at the Utah Department of Transportation (UDOT) to prioritize safety improvements on state-owned roadways. Unlike the Utah crash analysis methodologies that come before it, the CAMS focuses exclusively on segment-related crashes. The benefits of such an analysis can be found in identifying locations that have safety concerns unbiased from intersections and their related crashes. The CAMS uses UDOT data to create a spreadsheet of roadway segments and their associated crashes. Each segment is homogeneous with respect to five variables: Annual Average Daily Traffic (AADT), functional class, number of lanes, speed limit, and urban code. In the statistical analyses performed on the data, four years of crash data (2014-2017) are used to predict distributions of crashes for the most recent year of data (2018). Observed crash counts are compared to the predicted distributions and assigned a percentile value within the distributions, and segments are subsequently ranked in order of safety concern according to those percentiles. Two-page technical reports are created for segments that rank high in the state or UDOT Region. These reports consist of concise tables of roadway data and crash trends pertaining to each segment. Research analysts also add observations made in virtual site visits to the reports. In the end, the results and the reports are sent to UDOT where UDOT Region engineers may review and study identified segments in further detail. This research also includes modifications made to the Intersection Safety Analysis Methodology (ISAM) which focuses exclusively on intersection-related crashes. The modifications made to the ISAM mirror the abilities of the CAMS, thus allowing the pair of methodologies to analyze the entire state route network without overlapping any crash data.

Thesis (M. Com. (Economics)) -- University of Limpopo, 2019 / Financial markets and quite a diverse number of financial instruments have been growing in a controlled manner in recent decades in terms of value and volume. Brazil, Russia, India, China and South Africa (BRICS) are distinguished as having the fast growing markets in the universe compared to other markets of emerging economies, according to their promising economic prospective and demographic power. This study investigated the effects of government stock on investment activity in BRICS countries. This study used panel autoregressive distributed lag model (PARDL), Engel-Granger causality test, impulse response functions (IRF) and variance decomposition tests. Such techniques were applied to the annual data for the periods 2001 to 2016 in order to determine the effects of government stock on investment activity. The variables (government stock on bonds, government stock on mutual banks, government stock on corporations and government stock on liquid assets), including gross fixed capital formation which is a measure of investment activity, were subjected to panel unit root tests and that confirmed different orders of cointegration. The existence of a long run relationship between investment activity and other macroeconomic variables used in this study was determined by means of the panel cointegration tests, where one lag was used. The PARDL showed that in the long run investment activity was positively influenced by government stock on mutual banks and government stock on liquid assets, and negatively related to government stock on bonds and government stock on corporations. The Engel-Granger causality test revealed existence of unidirectional movement between investment activity and government stock on corporations as well as from government stock on bonds to liquid assets. The impulse response function test showed the impulse percentage of fluctuation that the variables did contribute to each other, from various periods both in the short and long run. While the variance decomposition of investment indicated that Investment was shocked by its own innovations throughout all the periods. A critical evaluation is needed to avoid investment shocks, instability of investment activity, instability of financial markets and the economy as a whole.

Tidsperioden mellan räkenskapsårets slut och datumet för påskriven revisionsberättelse benämns audit report lag (ARL). Anledningarna till att ARL uppstår har studerats i stor utsträckning, men de konkreta effekterna som uppstår till följd av ARL är mindre studerade. En tidigare studie om ARL:s samband med ökad risk för aktieprisfall på den kinesiska aktiemarknaden visade på ett positivt samband. På grund av detta samband finns ett intresse att studera om ett liknande samband existerar på den svenska aktiemarknaden. Syftet med studien är att förklara ett eventuellt samband mellan lång ARL och ökad risk för aktieprisfall på den svenska aktiemarknaden. Studien använder sig av en deduktiv ansats och en longitudinell forskningsdesign bestående av kvantitativ data för att försöka förklara ett eventuellt samband mellan lång ARL och en ökad risk för aktieprisfall. Datamaterialet bestod av sekundärdata. Studien finner inget samband mellan lång ARL och ökad risk för aktieprisfall på den svenska aktiemarknaden. Däremot visas svaga indikationer på att kort ARL leder till ökad risk för aktieprisfall på den svenska aktiemarknaden. Studien bidrar med utökad kunskap om sambanden mellan ARL och ökad risk för aktieprisfall. Vidare bidrar studien med kunskap för revisorer, bolagsledningar och investerare om vilka konsekvenser ARL kan ha på börsnoterade bolags aktiekurs. / The time period between the fiscal year end and the audit report date is termed audit report lag (ARL). The determinants of ARL have been frequently studied, however the practical consequences of ARL have not been studied to the same extent. A previous study about ARLs association with stock price crash risk on the Chinese stock market showed a positive association. This association made it interesting to study if a similar association exists on the Swedish stock market. The purpose of this study is to explain a possible association between long ARL and an increased stock price crash risk on the Swedish stock market. This study uses a deductive approach and a longitudinal research design consisting of quantitative data to explain a possible association between long ARL and an increased stock price crash risk. The data set consisted of secondary data. The study finds no association between long ARL and an increased stock price crash risk on the Swedish stock market. However, the study does find weak indications that short ARL leads to an increased stock price crash risk on the Swedish stock market. The study contributes with increased knowledge regarding associations between ARL and an increased stock price crash risk. Furthermore, the study contributes with knowledge for auditors, company management and investors of the consequences ARL can have on listed companies’ stock price.

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