This master thesis deals with experimental data that were collected through a crash avoidance experiment (which was lead by Professor Lennart Strandberg) in February and March 1990. Fifty-two ordinary drivers were instructed to perform two different kinds of manoeuvres on ice to determine the effectiveness of antilock brakes and of four tyre configurations. Results were reported at the 1991 ESV Conference. The first aim of this master thesis is to check and revise the measured data (used by Prof. Strandberg in courses at Linköping University). Checking out many hours of video recordings from onboard cameras reveals various protocol inconsistencies and errors, which in some cases it is not possible to correct. This work might increase the reliability of any further analysis of these data. The second aim is to elaborate on the revised data and to test the hypothesis that quick steering is a key factor to not lose control of the car during a crash avoidance manoeuvre. Different variables are introduced and used to estimate the steering wheel velocity and lateral friction use. The results show linear (positive) correlations between lateral friction use and steering wheel velocity. The greatest steering wheel velocities appear in the tests with loss-of-control and reach values up to 1180 degrees per second. However, the 1990 experimental layout was not intended for this type of research questions and it seems difficult to determine the causal relationship between quick steering and control of the car. Some cases of excessive steering input might have occurred. The results indicate that quick steering by itself is not enough to guarantee the total control of the car. An early reaction to the skid might be necessary too. Evidently, further research is needed.

Scania has a policy to attain a high crashworthiness standard and their trucks have to conform to Swedish cab safety standards. The main objective of this thesis is to clarify which parameter variations, present during the second part of the Swedish cab crashworthiness test on a Scania R-series cab, that have significance on the intrusion response. An LS-DYNA FE-model of the test case is analysed where parameter variations are introduced through the use of the probabilistic analysis tool LS-OPT. Example of analysed variations are the sheet thickness variation as well as the material variations such as stress-strain curve of the structural components, but also variations in the test setup such as the pendulum velocity and angle of approach on impact are taken into account. The effect of including the component forming in the analysis is investigated, where the variations on the material parameters are implemented prior to the forming. An additional objective is to analyse the influence of simulation and model dependent variations and weigh their respective effect on intrusion with the above stated physical variations. A submodel is created due to the necessity to speed up the simulations since the numerous parameter variations yield a large number of different designs, resulting in multiple analyses. Important structural component sensitivities are taken from the results and should be used as a pointer where to focus the attention when trying to increase the robustness of the cab. Also, the results show that the placement of the pendulum in the y direction (sideways seen from the driver perspective) is the most significant physical parameter variation during the Swedish pendulum test. It is concluded that to be able to achieve a fair comparison of the structural performance from repeated crash testing, this pendulum variation must be kept to a minimum. Simulation and model dependent parameters in general showed to have large effects on the intrusion. It is concluded that further investigations on individual simulation or model dependent parameters should be performed to establish which description to use. Mapping material effects from the forming simulation into the crash model gave a slight stiffer response compared to the mean pre-stretch approximations currently used by Scania. This is still however a significant result considering that Scanias approximations also included bake hardening effects from the painting process.

<p>This dissertation is a collection of papers with the unifying objective being to better understand crash risk in foreign exchange markets. I investigate how exposure to the risk of currency crashes is able to provide a unified rationalization of the returns of various sorted currency portfolios.</p><p>In the first chapter, I identify an aggregate global currency skewness risk factor, which I denote SKEW. Currency portfolios that have higher average excess returns covary more positively with this risk factor. They suffer losses in times when high interest rate investment currencies have a greater tendency to depreciate sharply as a group relative to low interest rate funding currencies. Consequently, they earn higher average excess returns as reward for exposure to this risk. I create three sets of sorted currency portfolios reflecting three distinct sources of variation in average excess currency returns. The first set sorts currencies based on interest rate differentials. The second set sorts currencies based on currency momentum. The third set sorts currencies based on currency undervaluedness relative to purchasing power power parity (PPP) implied exchange rates. I find that differences in exposure to the global currency skewness risk factor can explain the systematic variation in average excess currency returns within all three groups of portfolios much better than existing foreign exchange risk factors in the literature.</p><p>In the second chapter, I build on the first chapter by studying the extent to which currency crash risk is predictable or unpredictable and whether the pricing power of aggregate currency skewness, uncovered in the first chapter, is due to unpredictable or predictable crash risk. Focusing on currency crash risk proxied using realized currency skewness at both the individual currency level and at the aggregate level using the SKEW risk factor introduced in the first chapter, I investigate whether either form of crash risk is predictable using only past information about crash risk. In particular, I use past information on both individual currency level and aggregate level measures based on both lagged realized currency skewness and lagged option implied risk neutral skewness. I find evidence that there is not much predictability at the individual country level or at the aggregate level over the full sample period considered. However, there is some evidence of predictability at the aggregate level since 1999, and especially so when option implied risk neutral skewness measures are used. Additionally, I use the predictions of SKEW and conduct asset pricing similar to that in chapter 1 using predicted and unpredicted SKEW to see whether its pricing power comes from predictable or unpredictable components. I find evidence that it is unpredictable currency crash risk that is very important, as the asset pricing results are largely identical when either SKEW or SKEW forecast errors are used. and whether the pricing power of</p> / Dissertation

Taiwanese stock market. The results suggest that there exist two heterogeneous agents in Taiwanese stock market, £\-investors behaving as long-term contrarian and £]-investor behaving as short-term momentum traders. To depict in detail the practical financial market, this research empirically tests HAM with different fundamental values (measured by the moving average price in different rolling windows) across different investment frequencies (daily, weekly and monthly). The result suggests that £\-investors (fundamentalists) expect prices to deviate from the short-term moving average but mean revert to long-term moving average. Beta investors (chartists) act as momentum traders in daily and monthly frequency, but short-term contrarian in weekly frequency. In addition, this study tests whether the parameters in HAM can explain some characteristics of crashes and bubbles. The result suggests that there are different investor behaviors in Asian, Dotcom, and Subprime crashes. By comparing the parameters (£\, £], and £^) of each individual stock, the study finds that stocks with contrarian £\-investors and short-term momentum £]-investors acting as short-term momentum traders have more volatile price pattern. As to crashes and individual stock volatility, the result suggests that sudden crashes (abrupt price decline) tend to occur in the stocks with short-term momentum traders, and while general crash (longterm economic cycle) tend to occur in the stocks with long-term contrarian investors. Stocks with larger Gamma, proxy for uncertainty, tends to have general crash only when £\-investors acting as contrarian and £]-investors acting as momentum traders.

This thesis develops a GIS-based Bayesian approach for area-wide traffic crash analysis. Five years of crash data from Houston, Texas, are analyzed using a geographic information system (GIS), and spatial-temporal patterns of relative crash risk are identified based on a hierarchical Bayesian approach. This Bayesian approach is used to filter the uncertainty in the data and identify and rank roadway segments with potentially high relative risks for crashes. The results provide a sound basis to take preventive actions to reduce the risks in these segments. To capture the real safety indications better, this thesis differentiates the risks in different directions of the roadways, disaggregates different road types, and utilizes GIS to analyze and visualize the spatial relative crash risks in 3-D views according to different temporal scales. Results demonstrate that the approach is effective in spatially smoothing the relative crash risks, eliminating the instability of estimates while maintaining real safety trends. The posterior risk maps show high-risk roadway segments in 3-D views, which is more reader friendly than the conventional 2-D views. The results are also useful for travelers to choose relatively safer routes.

Algorithms in message-passing distributed systems often require partial synchrony to tolerate crash failures. Informally, partial synchrony refers to systems where timing bounds on communication and computation may exist, but the knowledge of such bounds is limited. Traditionally, the foundation for the theory of partial synchrony has been real time: a time base measured by counting events external to the system, like the vibrations of Cesium atoms or piezoelectric crystals. Unfortunately, algorithms that are correct relative to many real-time based models of partial synchrony may not behave correctly in empirical distributed systems. For example, a set of popular theoretical models, which we call M_*, assume (eventual) upper bounds on message delay and relative process speeds, regardless of message size and absolute process speeds. Empirical systems with bounded channel capacity and bandwidth cannot realize such assumptions either natively, or through algorithmic constructions. Consequently, empirical deployment of the many M_*-based algorithms risks anomalous behavior. As a result, we argue that real time is the wrong basis for such a theory. Instead, the appropriate foundation for partial synchrony is fairness: a time base measured by counting events internal to the system, like the steps executed by the processes. By way of example, we redefine M_* models with fairness-based bounds and provide algorithmic techniques to implement fairness-based M_* models on a significant subset of the empirical systems. The proposed techniques use failure detectors — system services that provide hints about process crashes — as intermediaries that preserve the fairness constraints native to empirical systems. In effect, algorithms that are correct in M_* models are now proved correct in such empirical systems as well. Demonstrating our results requires solving three open problems. (1) We propose the first unified mathematical framework based on Timed I/O Automata to specify empirical systems, partially synchronous systems, and algorithms that execute within the aforementioned systems. (2) We show that crash tolerance capabilities of popular distributed systems can be denominated exclusively through fairness constraints. (3) We specify exemplar system models that identify the set of weakest system models to implement popular failure detectors.

Whiplash injuries as a result of rear impact are among the most common injuries in traffic accidents. This is why whiplash injuries have reached a high priority in the research area. In this study, the effects of head restraint position and impact pulse to the whiplash injury have been analyzed by performing whiplash tests using the sled test facility of METU-BILTIR Center Vehicle Safety Unit. Although there are many whiplash test protocols, the test sample has been prepared according to the most recent one, Euro NCAP Whiplash Test Protocol. Three different head restraint positions and three different impact pulses with different severities, totally nine tests have been performed. The tests are performed with a three point generic seat belt and an instrumented Hybrid III 50th percentile male adult crash test dummy is used as the occupant in driver seat of a light commercial vehicle. High speed cameras, sensors on the crash test dummy and a data acquisition system are used to take the test data. This test data has been analyzed and presented according to the defined whiplash assessment criteria and the performance scores of the particular seat for each test have been determined using the whiplash assessment criteria values according to the Euro NCAP Test Protocols.

<p>Feedback control of Chest Acceleration or Chest Deflection is believed to be a good way of minimizing the risk of injury. In order to implement such a controller in a car, an observer estimating these responses is needed. The objective of the study was to develop a model of the dummy’s chest capable of estimating the Chest Acceleration and the Chest Deflection during frontal crashes in real time. The used sensor data come from car accelerometer and spindle rotation sensor of the belt, the data has been collected from dummies during crash tests. This study has accomplished the aims using a simple linear model of the chest using masses, springs and dampers. The parameters of the model have been estimated through system identification. Two types of black-box models have also been studied, one ARX model and one state-space model. The models have been tested and validated against data coming from different crash setups. The results show that all of the studied models can be used to estimate the dummy responses, the physical grey-box model and the black-box state-space model in particular.</p> / <p>Genom att använda återkoppling av storheterna bröstacceleration och bröstintryck antas man kunna minska risken för skador vid krockar i personbilar. För att kunna implementera detta behövs en observatör för dessa storheter. Målet med denna studie är att ta fram en modell för att kunna skatta accelerationen i bröstkorgen samt bröstintrycket i realtid i frontala krockar. Sensordata som använts kom från en accelerometer och en givare för att mäta rotationen i bältessnurran. Detta har gjorts genom att modellera bröstkorgen med linjära fjädrar och dämpare. Dess parametrar har skattats från data från krocktester från krockdockor. Två s.k. black-box-modeller har också tagits fram, en ARX-modell och en på tillståndsform. Modellerna har testats och validerats mha data från olika sorters krocktester. Resultaten visar att alla studerade modeller kan användas för att skatta de ovan nämnda storheterna, den fysikaliska modellen och black-box-modellen på tillståndsform fungerade bäst.</p>

Weather conditions have certain impacts on roadway traffic operations, especially traffic safety. Bridges differ from most surface streets and highways in terms of their physical properties and operational characteristics. This research assess the driving risk under different weather conditions through focus group firstly, then it develops a multi-ordered discrete choice model that is used to analyze and evaluate driving risks under both single and dual weather conditions. The data is derived from an extensive questionnaire survey in Shanghai. And the questionnaire includes those factors related to roadway, drivers, vehicles, and traffic that may have significant impacts on traffic safety under severe weather conditions. Considering the actual situation these variables except driver's gender are selected as independent variables of risk evaluation. As a result, different risk levels and corresponding probability are calculated, which are very important to optimize emergency resource allocation and make reasonable emergency measures. Moreover, in order to reduce severe bridge-related crashes, the research develops an ordered probit model to analyze those factors contributing to bridge-related crash severity and to predict probabilities of different severity levels under rainy conditions.

Safety reviews of existing roads are becoming a popular practice of many agencies nationally and internationally. Knowing road safety information is of great importance to both policymakers in addressing safety concerns and travelers in managing their trips. There have been various efforts in developing methodologies to measure and assess road safety in an effective manner. However, the existing research and practices are still constrained by their subjective and reactive nature. The goal of this research is to develop a framework of Road Risk Indices (RRIs) to assess road risks of existing highway infrastructure for both road users and agencies based on road geometrics, traffic conditions, and historical crash data. The proposed RRIs are intended to give a comprehensive and objective view of road safety, so that safety problems can be identified at an early stage before they rise in the form of accidents. A methodological framework of formulating RRIs that integrates results from crash prediction models and historical crash data is proposed, and Linear Referencing tools in the ArcGIS software are used to develop digital maps to publish estimated RRIs. These maps provide basic Geographic Information System (GIS) functions, including viewing and querying RRIs, and performing spatial analysis tasks. A semi-parameter count model and quantile regression based estimation are proposed to capture the specific characteristics of crash data and provide more robust and accurate predictions on crash counts. Crash data collected on Interstate Highways in Washington State for the year 2002 was extracted from the Highway Safety Information System (HSIS) and used for the case study. The results from the case study show that the proposed framework is capable of capturing statistical correlations between traffic crashes and influencing factors, leading to the effective integration of safety information in composite indices. / text