Fatigued driving : prevalence, risk factors and groups, and the law

Fatigue and sleepiness are major causes of road traffic accidents. However, precise data is often lacking because a validated and reliable device for detecting the level of sleepiness (cf. the breathalyzer for alcohol levels) does not exist, nor does criteria for the unambiguous detection of fatigue/sleepiness as a contributing factor in accident causation. Therefore, identification of risk factors and groups might not always be easy. Furthermore, it is extremely difficult to incorporate fatigue in operationalized terms into either traffic or criminal law. The main aims of this thesis were to estimate the prevalence of fatigue problems while driving among the Finnish driving population, to explore how VALT multidisciplinary investigation teams, Finnish police, and courts recognize (and prosecute) fatigue in traffic, to identify risk factors and groups, and finally to explore the application of the Finnish Road Traffic Act (RTA), which explicitly forbids driving while tired in Article 63. Several different sources of data were used: a computerized database and the original folders of multidisciplinary teams investigating fatal accidents (VALT), the driver records database (AKE), prosecutor and court decisions, a survey of young male military conscripts, and a survey of a representative sample of the Finnish active driving population. The results show that 8-15% of fatal accidents during 1991-2001 were fatigue related, that every fifth Finnish driver has fallen asleep while driving at some point during his/her driving career, and that the Finnish police and courts punish on average one driver per day on the basis of fatigued driving (based on the data from the years 2004-2005). The main finding regarding risk factors and risk groups is that during the summer months, especially in the afternoon, the risk of falling asleep while driving is increased. Furthermore, the results indicate that those with a higher risk of falling asleep while driving are men in general, but especially young male drivers including military conscripts and the elderly during the afternoon hours and the summer in particular; professional drivers breaking the rules about duty and rest hours; and drivers with a tendency to fall asleep easily. A time-of-day pattern of sleep-related incidents was repeatedly found. It was found that VALT teams can be considered relatively reliable when assessing the role of fatigue and sleepiness in accident causation; thus, similar experts might be valuable in the court process as expert witnesses when fatigue or sleepiness are suspected to have a role in an accident’s origins. However, the application of Article 63 of the RTA that forbids, among other things, fatigued driving will continue to be an issue that deserves further attention. This should be done in the context of a needed attitude change towards driving while in a state of extreme tiredness (e.g., after being awake for more than 24 hours), which produces performance deterioration comparable to illegal intoxication (BAC around 0.1%). Regarding the well-known interactive effect of increased sleepiness and even small alcohol levels, the relatively high proportion (up to 14.5%) of Finnish drivers owning and using a breathalyzer raises some concern. This concern exists because these drivers are obviously more focused on not breaking the “magic” line of 0.05% BAC than being concerned about driving impairment, which might be much worse than they realize because of the interactive effects of increased sleepiness and even low alcohol consumption. In conclusion, there is no doubt that fatigue and sleepiness problems while driving are common among the Finnish driving population. While we wait for the invention of reliable devices for fatigue/sleepiness detection, we should invest more effort in raising public awareness about the dangerousness of fatigued driving and educate drivers about how to recognize and deal with fatigue and sleepiness when they ultimately occur.

Evaluation of driving ability of the disabled persons in the context of the psychological activity theory

In the future the number of the disabled drivers requiring a special evaluation of their driving ability will increase due to the ageing population, as well as the progress of adaptive technology. This places pressure on the development of the driving evaluation system. Despite quite intensive research there is still no consensus concerning what is the factual situation in a driver evaluation (methodology), which measures should be included in an evaluation (methods), and how an evaluation has to be carried out (practise). In order to find answers to these questions we carried out empirical studies, and simultaneously elaborated upon a conceptual model for driving and a driving evaluation. The findings of empirical studies can be condensed into the following points: 1) A driving ability defined by the on-road driving test is associated with different laboratory measures depending on the study groups. Faults in the laboratory tests predicted faults in the on-road driving test in the novice group, whereas slowness in the laboratory predicted driving faults in the experienced drivers group. 2) The Parkinson study clearly showed that even an experienced clinician cannot reliably accomplish an evaluation of a disabled person’s driving ability without collaboration with other specialists. 3) The main finding of the stroke study was that the use of a multidisciplinary team as a source of information harmonises the specialists’ evaluations. 4) The patient studies demonstrated that the disabled persons themselves, as well as their spouses, are as a rule not reliable evaluators. 5) From the safety point of view, perceptible operations with the control devices are not crucial, but correct mental actions which the driver carries out with the help of the control devices are of greatest importance. 6) Personality factors including higher-order needs and motives, attitudes and a degree of self-awareness, particularly a sense of illness, are decisive when evaluating a disabled person’s driving ability. Personality is also the main source of resources concerning compensations for lower-order physical deficiencies and restrictions. From work with the conceptual model we drew the following methodological conclusions: First, the driver has to be considered as a holistic subject of the activity, as a multilevel hierarchically organised system of an organism, a temperament, an individuality, and a personality where the personality is the leading subsystem from the standpoint of safety. Second, driving as a human form of a sociopractical activity, is also a hierarchically organised dynamic system. Third, in an evaluation of driving ability it is a question of matching these two hierarchically organised structures: a subject of an activity and a proper activity. Fourth, an evaluation has to be person centred but not disease-, function- or method centred. On the basis of our study a multidisciplinary team (practitioner, driving school teacher, psychologist, occupational therapist) is recommended for use in demanding driver evaluations. Primary in a driver’s evaluations is a coherent conceptual model while concrete methods of evaluations may vary. However, the on-road test must always be performed if possible.

Silvicultural decisions based on simulation-optimization systems

Forest management is facing new challenges under climate change. By adjusting thinning regimes, conventional forest management can be adapted to various objectives of utilization of forest resources, such as wood quality, forest bioenergy, and carbon sequestration. This thesis aims to develop and apply a simulation-optimization system as a tool for an interdisciplinary understanding of the interactions between wood science, forest ecology, and forest economics. In this thesis, the OptiFor software was developed for forest resources management. The OptiFor simulation-optimization system integrated the process-based growth model PipeQual, wood quality models, biomass production and carbon emission models, as well as energy wood and commercial logging models into a single optimization model. Osyczka s direct and random search algorithm was employed to identify optimal values for a set of decision variables. The numerical studies in this thesis broadened our current knowledge and understanding of the relationships between wood science, forest ecology, and forest economics. The results for timber production show that optimal thinning regimes depend on site quality and initial stand characteristics. Taking wood properties into account, our results show that increasing the intensity of thinning resulted in lower wood density and shorter fibers. The addition of nutrients accelerated volume growth, but lowered wood quality for Norway spruce. Integrating energy wood harvesting into conventional forest management showed that conventional forest management without energy wood harvesting was still superior in sparse stands of Scots pine. Energy wood from pre-commercial thinning turned out to be optimal for dense stands. When carbon balance is taken into account, our results show that changing carbon assessment methods leads to very different optimal thinning regimes and average carbon stocks. Raising the carbon price resulted in longer rotations and a higher mean annual increment, as well as a significantly higher average carbon stock over the rotation.

Atomic scale engineering of carbon nanotubes

Carbon nanotubes, seamless cylinders made from carbon atoms, have outstanding characteristics: inherent nano-size, record-high Young’s modulus, high thermal stability and chemical inertness. They also have extraordinary electronic properties: in addition to extremely high conductance, they can be both metals and semiconductors without any external doping, just due to minute changes in the arrangements of atoms. As traditional silicon-based devices are reaching the level of miniaturisation where leakage currents become a problem, these properties make nanotubes a promising material for applications in nanoelectronics. However, several obstacles must be overcome for the development of nanotube-based nanoelectronics. One of them is the ability to modify locally the electronic structure of carbon nanotubes and create reliable interconnects between nanotubes and metal contacts which likely can be used for integration of the nanotubes in macroscopic electronic devices. In this thesis, the possibility of using ion and electron irradiation as a tool to introduce defects in nanotubes in a controllable manner and to achieve these goals is explored. Defects are known to modify the electronic properties of carbon nanotubes. Some defects are always present in pristine nanotubes, and naturally are introduced during irradiation. Obviously, their density can be controlled by irradiation dose. Since different types of defects have very different effects on the conductivity, knowledge of their abundance as induced by ion irradiation is central for controlling the conductivity. In this thesis, the response of single walled carbon nanotubes to ion irradiation is studied. It is shown that, indeed, by energy selective irradiation the conductance can be controlled. Not only the conductivity, but the local electronic structure of single walled carbon nanotubes can be changed by the defects. The presented studies show a variety of changes in the electronic structures of semiconducting single walled nanotubes, varying from individual new states in the band gap to changes in the band gap width. The extensive simulation results for various types of defect make it possible to unequivocally identify defects in single walled carbon nanotubes by combining electronic structure calculations and scanning tunneling spectroscopy, offering a reference data for a wide scientific community of researchers studying nanotubes with surface probe microscopy methods. In electronics applications, carbon nanotubes have to be interconnected to the macroscopic world via metal contacts. Interactions between the nanotubes and metal particles are also essential for nanotube synthesis, as single walled nanotubes are always grown from metal catalyst particles. In this thesis, both growth and creation of nanotube-metal nanoparticle interconnects driven by electron irradiation is studied. Surface curvature and the size of metal nanoparticles is demonstrated to determine the local carbon solubility in these particles. As for nanotube-metal contacts, previous experiments have proved the possibility to create junctions between carbon nanotubes and metal nanoparticles under irradiation in a transmission electron microscope. In this thesis, the microscopic mechanism of junction formation is studied by atomistic simulations carried out at various levels of sophistication. It is shown that structural defects created by the electron beam and efficient reconstruction of the nanotube atomic network, inherently related to the nanometer size and quasi-one dimensional structure of nanotubes, are the driving force for junction formation. Thus, the results of this thesis not only address practical aspects of irradiation-mediated engineering of nanosystems, but also contribute to our understanding of the behaviour of point defects in low-dimensional nanoscale materials.

Computer simulation of H and He effects in fusion reactor materials

Fusion power is an appealing source of clean and abundant energy. The radiation resistance of reactor materials is one of the greatest obstacles on the path towards commercial fusion power. These materials are subject to a harsh radiation environment, and cannot fail mechanically or contaminate the fusion plasma. Moreover, for a power plant to be economically viable, the reactor materials must withstand long operation times, with little maintenance. The fusion reactor materials will contain hydrogen and helium, due to deposition from the plasma and nuclear reactions because of energetic neutron irradiation. The first wall divertor materials, carbon and tungsten in existing and planned test reactors, will be subject to intense bombardment of low energy deuterium and helium, which erodes and modifies the surface. All reactor materials, including the structural steel, will suffer irradiation of high energy neutrons, causing displacement cascade damage. Molecular dynamics simulation is a valuable tool for studying irradiation phenomena, such as surface bombardment and the onset of primary damage due to displacement cascades. The governing mechanisms are on the atomic level, and hence not easily studied experimentally. In order to model materials, interatomic potentials are needed to describe the interaction between the atoms. In this thesis, new interatomic potentials were developed for the tungsten-carbon-hydrogen system and for iron-helium and chromium-helium. Thus, the study of previously inaccessible systems was made possible, in particular the effect of H and He on radiation damage. The potentials were based on experimental and ab initio data from the literature, as well as density-functional theory calculations performed in this work. As a model for ferritic steel, iron-chromium with 10% Cr was studied. The difference between Fe and FeCr was shown to be negligible for threshold displacement energies. The properties of small He and He-vacancy clusters in Fe and FeCr were also investigated. The clusters were found to be more mobile and dissociate more rapidly than previously assumed, and the effect of Cr was small. The primary damage formed by displacement cascades was found to be heavily influenced by the presence of He, both in FeCr and W. Many important issues with fusion reactor materials remain poorly understood, and will require a huge effort by the international community. The development of potential models for new materials and the simulations performed in this thesis reveal many interesting features, but also serve as a platform for further studies.

The watershed simulation and forecasting system in the National Board of and the Environment

Yhteenveto: Vesistömalleihin perustuva vesistöjen seuranta- ja ennustejärjestelmä vesi- ja ympäristöhallinnossa

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.