Dans l’optique de la conception et du développement d’un siège aéronautique et afin derespecter la règlementation sécuritaire en vigueur, la structure du siège développé doitpermettre une dissipation rapide de l’énergie perçue en cas de crash aérien (Fig. 1), ceci dansle but de protéger les passagers. La majorité des systèmes intégrés à la structure des sièges etpermettant cette absorption d’énergie (Fig. 2) est constituée de composants métalliques qui sedéforment plastiquement pour dissiper l’énergie due au crash. Actuellement, l’industrie et larecherche se tournent vers les matériaux composites pour substituer de tels systèmes.Cependant le comportement de ces matériaux lors de sollicitations mécaniques sévères estfortement différent des matériaux métalliques, notamment dû au fait que les mécanismesd’endommagement sont très distincts.Le but de cette étude portant sur des structures tubulaires composites est d’évaluer leurcapacité à dissiper l’énergie. A cette fin, différentes stratifications ont été testées encompression (Fig. 3 et 4) dans le but de déterminer leur comportement, comparer leurspropriétés et calculer leurs valeurs de SEA (absorption d'énergie spécifique, en kJ.kg-1)servant à évaluer leur aptitude à dissiper l’énergie engendrée en cas de crash. Ces dernièressont issues des courbes effort-déplacement obtenues lors des essais d’écrasement (Fig. 5). Lesdifférents essais de compression ont été instrumentés et suivis au moyen de caméras rapides etdes images post-essais ont été réalisées par tomographie pour comprendre les mécanismesd’endommagement mis en jeu (Fig. 4 et 6). Ces essais ont été réalisés à vitesse de chargementquasi-statique puis dynamique et selon diverses conditions limites. Les différents résultats decomportement en compression sont également utilisés dans le but de construire et enrichir unmodèle de calcul par éléments finis (Fig. 7 et 8) permettant de simuler la réponse de structurescomposites de différentes natures soumises au crash en intégrant la géométrie et lacomposition de la structure (Fig. 8).L’objectif de ce travail de recherche est ainsi d’évaluer l’énergie pouvant être dissipée par desstructures tubulaires composites, de comparer les absorptions induites par des structurescomposites de compositions différentes, et/ou bi-matériaux, et enfin de fournir un modèleéléments finis représentant le comportement de structures composites en compression jusqu’àl’endommagement et la ruine de la structure.Il a ainsi été établi qu’en chargement statique, un stratifié unidirectionnel orienté à 0° etstabilisé par des plis de tissus répond fortement aux attentes en terme de dissipation d’énergie,mais pas en sollicitation dynamique. Dans ce cas, une stratification à 90° semble plusadéquate. D’autre part, un confinement forcé vers l’intérieur est avantageux dans la plupartdes cas, réduisant le pic d’effort initial sans diminuer drastiquement la valeur de SEA. / With the perspective of the design and development of an aircraft seat and in order to respectthe safety regulations in effect, the structure of the developed seat must allow for a swiftdissipation of the energy received in the event of an aircraft crash (Fig. 1) so as to protect thepassengers. The majority of systems integrated into the seats structure and allowing energydissipation (Fig. 2) consists of metal components that sustain plastic deformation to dissipatethe energy induced by the crash. Currently, industry and research sectors are turning theirfocus towards composite materials to substitute such systems. However, the behavior of thesematerials during severe mechanical stress is strongly different from metallic materials, inparticular due to the fact that damage mechanisms are very distinct.The purpose of this study on composite tubular structures is to evaluate their ability todissipate the energy. To this end, different laminate structures were tested in compression(Fig. 3 and 4) in order to identify their behavior, compare their properties and calculate theirSEA value (Specific Energy Absorption, in kJ.kg-1) used to evaluate their capacity to dissipatethe energy generated during a crash. Those are resulting from the load-displacement curvesobtained during the crushing tests (Fig. 5). The various compression tests were instrumentedand monitored by means of rapid imaging cameras and post-crushing tomographic imaginghas been realized in order to understand the damage mechanisms involved (Fig. 4 and 6).Testing has been carried out under quasi-static and dynamic loading and using severalboundary conditions. The different results of compression and crushing behavior are also usedin order to build and improve a finite element calculation model (Fig. 7 and 8) allowing tosimulate the response of composite structures of different natures subjected to crash byintegrating the geometry and the composition of the structure (Fig. 8).The objective of this research work is thus to evaluate the energy that can be dissipated bycomposite tubular structures, to compare the absorption values induced by compositestructures of different compositions, and/or bi-materials, and, finally, to provide a finiteelement model representing the behavior of composite structure submitted to compressionuntil damage and fracture of the structure.It has consequently been established that in static loading, a unidirectional laminate orientedat 0° and stabilized by woven plies strongly meets the expectations in terms of energydissipation, but that is not the case in dynamic loading. In this case, a 90° stratification seemsmore adequate. Incidentally, an inner constrained containment is more effective in most cases,reducing the initial peak load without drastically reducing the SEA value.

Die vorliegende Arbeit leistet einen Beitrag zur Identifizierung von Einflussgrößen und Fehlerursachen auf Verkehrsunfälle. Diese können als Grundlage für Hinweise für den Einsatz und die Gestaltung von Fahrerassistenzsystemen genutzt werden. Dafür wurden insgesamt 506 Unfälle umfassend (in depth) untersucht. Zur Analyse der Pre-Crash-Phase der Unfälle wurden die Ergebnisse einer psychologischen Befragung mit Angaben aus der polizeilichen Verkehrsunfallanzeige, Informationen zur Unfallstelle, medizinischen Berichten sowie Informationen aus der technischen Rekonstruktion integriert. Anschließend wurde eine Fehleranalyse unter Betrachtung der Teilsysteme Fahrer, Umwelt und Fahrzeug durchgeführt. Um den bestmöglichen Befragungszeitpunkt herauszufinden, wurden in einer Vorstudie jeweils 15 Interviews am Unfallort sowie telefonische Interviews ein bis 14 Tage bzw. 15 bis 90 Tage nach dem Unfall bezüglich der Anzahl ihrer Genauigkeits- und Glaubhaftigkeitsmerkmale, der Motivation zur Interviewteilnahme sowie möglicher Vergessenseffekte verglichen. Im Ergebnis konnten keine Nachteile nachträglicher telefonischer Befragungen im Vergleich zu Befragungen an der Unfallstelle gefunden werden. Zur Fehleranalyse wurde ein verkehrspsychologisches Fehlerklassifikationsschema auf der Basis der verhütungsbezogenen Klassifikation von Fehlhandlungsursachen (Hacker, 1998) erstellt. Mit dessen Hilfe wurden insgesamt 696 Unfalleinflussfaktoren für die Unfallverursacher (n=343) ermittelt. Im Ergebnis wurde so bei allen Unfalltypengruppen ein hoher Anteil von Fehlern infolge von Ablenkung sowie Aktivierungsmängeln festgestellt (jeweils zwischen 28 % und 47%). Des Weiteren gab es bei Kreuzungsunfällen zahlreiche Fehler infolge von Sichtverdeckungen (40%), Fokusfehlern (30%), Reizmaskierungen (26%) und Verstößen gen die Verkehrsregeln (11%). Unfälle durch Abkommen von der Fahrbahn traten zudem häufig infolge von Erwartungsfehlern (35%), Reizmaskierungen (26%), Verstößen gegen die Verkehrsregeln (24%) sowie Zielsetzungs- bzw. Handlungsfehler (23%) auf. Unfälle im Längsverkehr passierten des Weiteren durch Erwartungsfehler (36%), Zielsetzungs- und Handlungsfehler (36%) sowie durch Setzen eines falschen Aufmerksamkeitsfokus (24%) auf. Anhand dieser Studienergebnisse ist das Sicherheitspotential für Fahrerassistenzsysteme, welche den Fahrer bei der Informationsaufnahme unterstützen und ihm helfen Ablenkungen und Aktivierungsdefizite zu vermeiden, als hoch einzuschätzen. So könnten insgesamt über zwei Drittel der erfassten Fehlhandlungen vermieden werden. Darüber hinaus münden die Studienergebnisse in ein Klassifikationsschema zur Erfassung von Unfalleinflussfaktoren, welches im Rahmen der Unfallforschung dauerhaft eingesetzt werden sollte.

Indiana University-Purdue University Indianapolis (IUPUI) / Automotive technology has grown from strength to strength in the recent years. The main focus of research in the near past and the immediate future are autonomous vehicles. Autonomous vehicles range from level 1 to level 5, depending on the percentage of machine intervention while driving. To make a smooth transition from human driving and machine intervention, the prediction of human driving behavior is critical. This thesis is a subset of driving behavior prediction. The objective of this thesis is to predict the possibility of crash and implement an appropriate active safety system to prevent the same. The prediction of crash requires data of transition between lanes, and speed ranges. This is achieved through a variation of hidden Markov model. With the crash prediction and analysis of the Markov models, the required ADAS system is activated. The above concept is divided into sections and an algorithm was developed. The algorithm is then scripted into MATLAB for simulation. The results of the simulation is recorded and analyzed to prove the idea.

With the advancements that have taken place in technology the recent decades, it is nowpossible to work anywhere and at any time. Coworking space is the type of flexible workplacethat is currently growing the fastest and comprises a workplace shared between severalcompanies and individuals with emphasis on collaboration and knowledge sharing. Withbenefits such as cost efficiency for members, it is now questioned how the companies that offercoworking make it work financially. This thesis investigates the profitability of coworkingcompanies and whether they are persevering enough to survive an economic downturn orrecession.By examining the Stockholm market’s nine largest coworking companies' annual reports,interviewing them and experts from different areas on the market, these questions have beenanswered. In order to further assess the potential of the new market segment, the currenteconomic climate has been compared with the IT-bubble in 2001. Further, the financial positionof the coworking companies has been set against the business model of hotels. Through a datacollection that is both qualitative and quantitative, the results have been discussed thematically.From the study it was concluded that coworking operators are economically weak with low orno profitability. By developing their business model in accordance with the one of hotels,companies are expected to improve their financial position. This is done by overbookingflexible workplaces and in detail work with profit per workplace to increase the total return.The coworking companies' rental cost to their property owners one of the largest expenses andthus also decisive. For companies to be able to operate in the long run, revenue sharing rent isrecommended. Experience, strong ownership, central location and diversification of membersare recognized as success factors. Regarding the coworking companies' sustainability ineconomic downturns, they are also considered weak. Given their deficient financial statementsand balance sheets, they lack the margins and qualifications to endure an economic downturnor recession. A consolidation is expected to take place where survival of each coworkingoperator depend on new customers to leave conventional leases and prioritize flexibility.  Furthermore, the study has shown the economic climate today to resemble with what led to theIT-bubble in 2001, which in turn signals for a coworking bubble. A pattern of increased demandfor service in the office market has also been discovered. What we are seeing today is thebeginning of a change on the office market - a servicification that requires a fundamental changein the office sector's business model. / Med de framgångar som skett inom teknik de senaste decennierna är det idag möjligt att arbetavar och när som helst. Coworking space är den typ av flexibel arbetsplats som just nu växersnabbast och innebär att arbetsplatsen delas mellan flera företag och individer samtunderstryker samarbete och kunskapsdelning. Med fördelar såsom kostnadseffektivisering förmedlemmar ifrågasätts nu hur företagen som erbjuder coworking får det att gå ihop ekonomiskt.I den här uppsatsen belyses coworkingföretagens lönsamhet och om de är uthålliga nog attöverleva en ekonomisk nedgång eller lågkonjunktur.Genom att för Stockholmsmarknaden undersöka de nio största coworkingföretagensårsrapporter, intervjua dem och experter från olika områden av marknaden har dessa frågorutvisats. För att ytterligare kunna bedöma potentialen för det nya marknadssegmentet hardagens ekonomiska klimat jämförts med vad som ledde upp till IT-krisen 2001 samtcoworkingföretagens ekonomiska ställning ställts mot den affärsmodell som hotell använder.Genom en datainsamling som både är kvalitativ och kvantitativ har resultaten diskuteratstematiskt.Studien har mynnat ut i en slutsats om att coworkingoperatörer är ekonomiskt svaga företagmed låg eller ingen lönsamhet. Genom att utveckla sin affärsmodell efter den som hotellanvänder förväntas företagen kunna förbättra sin ekonomiska ställning. Detta görs genom attöverboka flexibla arbetsplatser och på detaljnivå arbeta med vinst per arbetsplats för att ökaden totala avkastningen. Coworkingföretagens hyreskostnad till sina fastighetsägare är en avde största utgifterna och därmed också avgörande. För att företagen ska kunna verka i längdenrekommenderas omsättningsbaserad hyra. Erfarenhet, starkt ägandeskap, central lokaliseringoch diversifiering av medlemmar ses som framgångsfaktorer. Gällande coworkingföretagensuthållighet i konjunkturnedgångar, bedöms dem också svaga. Med hänsyn till bristanderesultat- och balansräkningar har de inte marginaler eller förutsättningar nog att utstå enekonomisk nedgång eller lågkonjunktur. En konsolidering väntas ske där coworkingoperatörernasöverlevnad hänger på tillskott av nya kunder som väljer att lämna konventionellahyresavtal och prioritera flexibilitet.  Ytterligare har studien visat på att det ekonomiska klimatet idag också liknar det som leddefram till IT-krisen 2001, vilket i sin tur signalerar för en coworkingbubbla. Det har ocksåuppdagats ett mönster av ökad efterfrågan på service på kontorsmarknaden. Vad vi nu ser börjanpå är en förändring i kontorsmarknaden - en tjänstefiering som kräver en fundamentalförändring av kontorssektorns affärsmodell.

Traffic safety is a major concern for the public, and it is an important component of the roadway management strategy. In order to improve highway safety, extensive efforts have been made by researchers, transportation engineers, Federal, State, and local government officials. With these consistent efforts, both fatality and injury rates from road traffic crashes in the United States have been steadily declining over the last six years (2006~2011). However, according to the National Highway Traffic Safety Administration (NHTSA, 2013), 33,561 people died in motor vehicle traffic crashes in the United States in 2012, compared to 32,479 in 2011, and it is the first increase in fatalities since 2005. Moreover, in 2012, an estimated 2.36 million people were injured in motor vehicle traffic crashes, compared to 2.22 million in 2011. Due to the demand of highway safety improvements through systematic analysis of specific roadway cross-section elements and treatments, the Highway Safety Manual (HSM) (AASHTO, 2010) was developed by the Transportation Research Board (TRB) to introduce a science-based technical approach for safety analysis. One of the main parts in the HSM, Part D, contains crash modification factors (CMFs) for various treatments on roadway segments and at intersections. A CMF is a factor that can estimate potential changes in crash frequency as a result of implementing a specific treatment (or countermeasure). CMFs in Part D have been developed using high-quality observational before-after studies that account for the regression to the mean threat. Observational before-after studies are the most common methods for evaluating safety effectiveness and calculating CMFs of specific roadway treatments. Moreover, cross-sectional method has commonly been used to derive CMFs since it is easier to collect the data compared to before-after methods. Although various CMFs have been calculated and introduced in the HSM, still there are critical limitations that are required to be investigated. First, the HSM provides various CMFs for single treatments, but not CMFs for multiple treatments to roadway segments. The HSM suggests that CMFs are multiplied to estimate the combined safety effects of single treatments. However, the HSM cautions that the multiplication of the CMFs may over- or under-estimate combined effects of multiple treatments. In this dissertation, several methodologies are proposed to estimate more reliable combined safety effects in both observational before-after studies and the cross-sectional method. Averaging two best combining methods is suggested to use to account for the effects of over- or under- estimation. Moreover, it is recommended to develop adjustment factor and function (i.e. weighting factor and function) to apply to estimate more accurate safety performance in assessing safety effects of multiple treatments. The multivariate adaptive regression splines (MARS) modeling is proposed to avoid the over-estimation problem through consideration of interaction impacts between variables in this dissertation. Second, the variation of CMFs with different roadway characteristics among treated sites over time is ignored because the CMF is a fixed value that represents the overall safety effect of the treatment for all treated sites for specific time periods. Recently, few studies developed crash modification functions (CMFunctions) to overcome this limitation. However, although previous studies assessed the effect of a specific single variable such as AADT on the CMFs, there is a lack of prior studies on the variation in the safety effects of treated sites with different multiple roadway characteristics over time. In this study, adopting various multivariate linear and nonlinear modeling techniques is suggested to develop CMFunctions. Multiple linear regression modeling can be utilized to consider different multiple roadway characteristics. To reflect nonlinearity of predictors, a regression model with nonlinearizing link function needs to be developed. The Bayesian approach can also be adopted due to its strength to avoid the problem of over fitting that occurs when the number of observations is limited and the number of variables is large. Moreover, two data mining techniques (i.e. gradient boosting and MARS) are suggested to use 1) to achieve better performance of CMFunctions with consideration of variable importance, and 2) to reflect both nonlinear trend of predictors and interaction impacts between variables at the same time. Third, the nonlinearity of variables in the cross-sectional method is not discussed in the HSM. Generally, the cross-sectional method is also known as safety performance functions (SPFs) and generalized linear model (GLM) is applied to estimate SPFs. However, the estimated CMFs from GLM cannot account for the nonlinear effect of the treatment since the coefficients in the GLM are assumed to be fixed. In this dissertation, applications of using generalized nonlinear model (GNM) and MARS in the cross-sectional method are proposed. In GNMs, the nonlinear effects of independent variables to crash analysis can be captured by the development of nonlinearizing link function. Moreover, the MARS accommodate nonlinearity of independent variables and interaction effects for complex data structures. In this dissertation, the CMFs and CMFunctions are estimated for various single and combination of treatments for different roadway types (e.g. rural two-lane, rural multi-lane roadways, urban arterials, freeways, etc.) as below: 1) Treatments for mainline of roadway: - adding a thru lane, conversion of 4-lane undivided roadways to 3-lane with two-way left turn lane (TWLTL) 2) Treatments for roadway shoulder: - installing shoulder rumble strips, widening shoulder width, adding bike lanes, changing bike lane width, installing roadside barriers 3) Treatments related to roadside features: - decrease density of driveways, decrease density of roadside poles, increase distance to roadside poles, increase distance to trees Expected contributions of this study are to 1) suggest approaches to estimate more reliable safety effects of multiple treatments, 2) propose methodologies to develop CMFunctions to assess the variation of CMFs with different characteristics among treated sites, and 3) recommend applications of using GNM and MARS to simultaneously consider the interaction impact of more than one variables and nonlinearity of predictors. Finally, potential relevant applications beyond the scope of this research but worth investigation in the future are discussed in this dissertation.

Real-time crash prediction is a complex task, since there is no existing framework to predict crash likelihood, types, and severity together along with a real-time traffic management strategy. Developing such a framework presents various challenges, including not independent and identically distributed data, imbalanced data, large model size, high computational cost, missing data, sensitivity vs. false alarm rate (FAR) trade-offs, estimation of traffic restoration time after crash occurrence, and real-world deployment strategy. A novel spatial ensemble distillation learning modeling technique is proposed to address these challenges. First, large-scale real-time data were used to develop a crash likelihood prediction model. Second, the proposed crash likelihood model's viability in predicting specific crash types was tested for real-world applications. Third, the framework was extended to predict crash severity in real-time, categorizing crashes into four levels. The results demonstrated strong performance with sensitivities of 90.35%, 94.80%, and 84.23% for all crashes, rear-end crashes, and sideswipe/angle crashes, and 83.32%, 81.25%, 83.08%, and 84.59% for fatal, severe, minor injury, and PDO crashes, respectively, all while remaining very low FARs. This methodology can also reduce model size, lower computation costs, improve sensitivity, and decrease FAR. These results will be used by traffic management center for taking measures to prevent crashes in real-time through active traffic management strategies. The framework was further extended for efficient traffic management after any crash occurrence despite adopting these strategies. Particularly, the framework was extended to predict the traffic state after a crash, predict the traffic restoration time based on the estimated post-crash traffic state, and apply a three-step validation technique to evaluate the performance of the developed approach. Finally, real-world deployment strategies of the proposed methodologies for real-time crash prediction along with their types and severities and real-time post-crash management are discussed. Overall, the methodologies presented in this dissertation offer multifaceted novel contributions and have excellent potential to reduce fatalities and injuries.

Finite element analysis with explicit time integration is widely used in commercial crash solvers to accurately simulate transient structural problems involving large-deformation and nonlinearity. Technological advances in computer software and hardware have expanded the boundaries of computational expense, allowing designers to analyse increasingly complex structures on desktop computers. This dissertation is a review of the use of finite element analysis for crash simulation, the principles of crashworthy design and a practical application of these methods and principles in the development of a concept energy absorber for a sailplane. Explicit nonlinear finite element analysis was used to do crash simulations of the glass, carbon and aramid fibre cockpit during the development of concept absorbers. The SOL700 solution sequence in MSC Nastran, which invokes the LS-Dyna solver for structural solution, was used. Single finite elements with Hughes-Liu shell formulation were loaded to failure in pure tension and compression and validated against material properties. Further, a simple composite crash box in a mass drop experiment was simulated and compared to experimental results. FEA was used for various crash simulations of the JS1 sailplane cockpit to determine its crashworthiness. Then, variants of a concept energy absorber with cellular aluminium sandwich construction were simulated. Two more variants constructed only of fibre-laminate materials were modelled for comparison. Energy absorption and specific energy absorption were analysed over the first 515 mm of crushing. Simulation results indicate that the existing JS1 cockpit is able to absorb energy through progressive crushing of the frontal structure without collapse of the main cockpit volume. Simulated energy absorption over the first 515 mm was improved from 2232 J for the existing structure, to 9 363 J by the addition of an energy absorber. Specific energy absorption during the simulation was increased from 1063 J/kg to 2035 J/kg. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2015

Finite element analysis with explicit time integration is widely used in commercial crash solvers to accurately simulate transient structural problems involving large-deformation and nonlinearity. Technological advances in computer software and hardware have expanded the boundaries of computational expense, allowing designers to analyse increasingly complex structures on desktop computers. This dissertation is a review of the use of finite element analysis for crash simulation, the principles of crashworthy design and a practical application of these methods and principles in the development of a concept energy absorber for a sailplane. Explicit nonlinear finite element analysis was used to do crash simulations of the glass, carbon and aramid fibre cockpit during the development of concept absorbers. The SOL700 solution sequence in MSC Nastran, which invokes the LS-Dyna solver for structural solution, was used. Single finite elements with Hughes-Liu shell formulation were loaded to failure in pure tension and compression and validated against material properties. Further, a simple composite crash box in a mass drop experiment was simulated and compared to experimental results. FEA was used for various crash simulations of the JS1 sailplane cockpit to determine its crashworthiness. Then, variants of a concept energy absorber with cellular aluminium sandwich construction were simulated. Two more variants constructed only of fibre-laminate materials were modelled for comparison. Energy absorption and specific energy absorption were analysed over the first 515 mm of crushing. Simulation results indicate that the existing JS1 cockpit is able to absorb energy through progressive crushing of the frontal structure without collapse of the main cockpit volume. Simulated energy absorption over the first 515 mm was improved from 2232 J for the existing structure, to 9 363 J by the addition of an energy absorber. Specific energy absorption during the simulation was increased from 1063 J/kg to 2035 J/kg. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2015

Master of Science / Department of Civil Engineering / Sunanda Dissanayake / Rapid increases are estimated in the percentage of elderly among the U.S. population starting in 2010. A majority of the older Americans depend on automobiles to meet their transportation needs either because of lack of public transportation or by choice. Ninety percent of total trips made by the elderly are by personal vehicle and seventy percent of this number involves the elderly driving the vehicles. However due to the aging process, older drivers experience a natural decline in sensory, cognitive, and other mental and physical capabilities as compared to younger drivers. This situation, combined with an imperfect highway infrastructure is making older drivers one of the most critical groups in terms of highway safety, thus demanding safer driving conditions. Safety concern for older drivers arises when the fatality rate per mile driven is considered, as exposure is one of the crucial factors contributing to increased fatality risk of older drivers. Hence, exposure reported in Billion Vehicle Miles Traveled (BVMT) was considered for this study. Crash data and exposure data were used to compute the fatality rates. Sources for this data are the Fatality Analysis Reporting System (FARS) and National Household Travel Survey (NHTS). A basic characteristics study was completed to compare the fatality risk of younger (16-24 yrs), middle-aged (25-64 yrs), and older drivers (65+ yrs). Crash details were screened to study the characteristics of older drivers involved in fatal crashes. Risk for older drivers due to other involved drivers of all ages divided into groups was studied to understand their distribution. A number of statistical methods like the chi-square test of independence, odds ratio and double paired comparison estimates were applied to study contributing factors of older driver’s increased fatal crash involvement. Results from the characteristics study for the elderly indicate that a majority of fatal crashes occur under daylight conditions with relatively higher seatbelt usage and non-alcoholic driving on straight level roads, which are generally considered as safer driving conditions. Other factors studied include vehicle-related variables like body type; manner of collision; roadway-related variables like roadway function class, month of the crash, and day of the week; and driver-related variables like race. Roadway functional class, vehicle body type, travel speed, number of drunk drivers, and the month in which the fatality occurred were found to have strong correlation with age of the older driver. Results from paired comparisons were used to estimate the fatality risk of older occupants as drivers and passengers under two different conditions considered simultaneously. Older drivers were found to have more fatality risk compared to older passengers. Recommended measures are also discussed to enhance older driver safety in the U.S.

Tragically, traffic accidents involving drivers, motorcyclists and pedestrians result in thousands of fatalities worldwide each year. For this reason, making improvements to road safety and saving people's lives is an international priority. In recent years, this aim has been supported by Intelligent Transport Systems, offering safety systems and providing an intelligent driving environment. The development of wireless communications and mobile ad hoc networks has led to improvements in intelligent transportation systems heightening these systems' safety. Vehicular ad hoc Networks comprise an important technology; included within intelligent transportation systems, they use dedicated short-range communications to assist vehicles to communicate with one another, or with those roadside units in range. This form of communication can reduce road accidents and provide a safer driving environment. A major challenge has been to design an ideal system to filter relevant contextual information from the surrounding environment, taking into consideration the contributory factors necessary to predict the likelihood of a crash with different levels of severity. Designing an accurate and effective pre-crash system to avoid front and back crashes or mitigate their severity is the most important goal of intelligent transportation systems, as it can save people's lives. Furthermore, in order to improve crash prediction, context-aware systems can be used to collect and analyse contextual information regarding contributory factors. The crash likelihood in this study is considered to operate within an uncertain context, and is defined according to the dynamic interaction between the driver, the vehicle and the environment, meaning it is affected by contributory factors and develops over time. As a crash likelihood is considered to be an uncertain context and develops over time, any usable technology must overcome this uncertainty in order to accurately predict crashes. This thesis presents a context-aware pre-crash collision prediction system, which captures information from the surrounding environment, the driver and other vehicles on the road. It utilises a Dynamic Bayesian Network as a reasoning model to predict crash likelihood and severity level, whether any crash will be fatal, serious, or slight. This is achieved by combining the above mentioned information and performing probabilistic reasoning over time. The thesis introduces novel context aware on-board unit architecture for crash prediction. The architecture is divided into three phases: the physical, the thinking and the application phase; these which represent the three main subsystems of a context-aware system: sensing, reasoning and acting. In the thinking phase, a novel Dynamic Bayesian Network framework is introduced to predict crash likelihood. The framework is able to perform probabilistic reasoning to predict uncertainty, in order to accurately predict a crash. It divides crash severity levels according to the UK department for transport, into fatal, serious and slight. GeNIe version 2.0 software was used to implement and verify the Dynamic Bayesian Network model. This model has been verified using both syntactical and real data provided by the UK department for transport in order to demonstrate the prediction accuracy of the proposed model and to demonstrate the importance of including a large amount of contextual information in the prediction process. The evaluation of the proposed system delivered high-fidelity results, when predicting crashes and their severity. This was judged by inputting different sensor readings and performing several experiments. The findings of this study has helped to predict the probability of a crash at different severity levels, accounting for factors that may be involved in causing a crash, thereby representing a valuable step towards creating a safer traffic network.