Master of Science / Department of Civil Engineering / Sunanda Dissanayake / In order to improve safety of the overall surface transportation system, each of the critical areas needs to be addressed separately with more focused attention. Statistics clearly show that large-truck crashes contribute significantly to an increased percentage of high-severity crashes. It is therefore important for the highway safety community to identify characteristics and contributory causes related to large-truck crashes. During the first phase of this study, fatal crash data from the Fatality Analysis Reporting System (FARS) database were studied to achieve that objective. In this second phase, truck-crashes of all severity levels were analyzed with the intention of understanding characteristics and contributory causes, and identifying factors contributing to increased severity of truck-crashes, which could not be achieved by analyzing fatal crashes alone. Various statistical methodologies such as cross-classification analysis and severity models were developed using Kansas crash data. Various driver-, road-, environment- and vehicle- related characteristics were identified and contributory causes were analyzed. From the cross-classification analysis, severity of truck-crashes was found to be related with variables such as road surface (type, character and condition), accident class, collision type, driver- and environment-related contributory causes, traffic-control type, truck-maneuver, crash location, speed limit, light and weather conditions, time of day, functional class, lane class, and Average Annual Daily Traffic (AADT). Other variables such as age of truck driver, day of the week, gender of truck-driver, pedestrian- and truck-related contributory causes were found to have no relationship with crash severity of large trucks. Furthermore, driver-related contributory causes were found to be more common than any other type of contributory cause for the occurrence of truck-crashes. Failing to give time and attention, being too fast for existing conditions, and failing to yield right of way were the most dominant truck-driver-related contributory causes, among many others. Through the severity modeling, factors such as truck-driver-related contributory cause, accident class, manner of collision, truck-driver under the influence of alcohol, truck maneuver, traffic control device, surface condition, truck-driver being too fast for existing conditions, truck-driver being trapped, damage to the truck, light conditions, etc. were found to be significantly related with increased severity of truck-crashes. Truck-driver being trapped had the highest odds of contributing to a more severe crash with a value of 82.81 followed by the collision resulting in damage to the truck, which had 3.05 times higher odds of increasing the severity of truck-crashes. Truck-driver under the influence of alcohol had 2.66 times higher odds of contributing to a more severe crash. Besides traditional practices like providing adequate traffic signs, ensuring proper lane markings, provision of rumble strips and elevated medians, use of technology to develop and implement intelligent countermeasures were recommended. These include Automated Truck Rollover Warning System to mitigate truck-crashes involving rollovers, Lane Drift Warning Systems (LDWS) to prevent run-off-road collisions, Speed Limiters (SLs) to control the speed of the truck, connecting vehicle technologies like Vehicle-to-Vehicle (V2V) integration system to prevent head-on collisions etc., among many others. Proper development and implementation of these countermeasures in a cost effective manner will help mitigate the number and severity of truck-crashes, thereby improving the overall safety of the transportation system.

Platelets made of slit and chopped unidirectional, carbon-fiber prepreg are becoming a popular option for use as a high performance molding compound because of their high fiber volume fraction and increased ability to flow compared to continuous fiber systems. As this molding compound is newly introduced to industry, increasing amounts of research have gone into understanding how platelets flow during molding and how components perform mechanically based on the final orientation state of platelets. This work investigates the performance of prepreg platelet molding compound (PPMC) as a viable alternative to continuous fiber systems for use with geometrically complex structural members on vehicles subjected to collisions. In doing so, the crash performance, energy absorption, and failure morphology of crush tubes made with PPMC are investigated and quantified. Then, a simulation methodology is developed to obtain manufacturing-informed performance models to predict the effect of platelet orientation state on mechanical behavior of PPMC components. This methodology uses a building block approach where each block in modeling is verified against closed-form solution (when available) and validated against experimental results. Once confidence is developed in a modeling block, the complexity of the simulation is increased until a component with full platelet orientation distribution is captured. The result is PPMC component models that are capable of predicting mechanical performance in orientation regimes that are not investigated experimentally.

O Atendimento Pré Hospitalar (APH) é um importante recurso no atendimento à vítimas de trauma. No entanto, há muitas dificuldades para demonstrar o efeito benéfico das intervenções do APH na sobrevivência das vítimas, sobretudo as de suporte avançado à vida (SAV). A proposta deste estudo é caracterizar as vítimas de acidentes trânsito, com Revised Trauma Score (RTS) <11, atendidas pelo SAV municipal e encaminhadas a hospitais terciários em São Paulo, além de identificar as variáveis da fase pré-hospitalar associadas à sobrevivência e avaliar o valor predeterminante dessas variáveis sobre o resultado obtido pelas vítimas. As variáveis avaliadas foram: sexo, idade, mecanismos do acidente, procedimentos de suporte básico e SAV realizados, repercussão fisiológica do trauma na cena do acidente, (considerando o RTS , seus parâmetros e flutuações), o tempo consumido no APH, gravidade do trauma segundo o Injury Severity Score (ISS),a Maximum Abbreviated Injury Scale (MAIS) e número de lesões para cada segmento corporal. Os resultados obtidos por 175 vítimas entre 12 e 65 anos, foram submetidos a "Análise de Sobrevivência de Kaplan Meier" e ao “Modelo de Riscos Proporcionais de Cox". A variável dependente foi o tempo de sobrevivência após o acidente, considerando os intervalos até 6h,12h, 24h, 48h, até 7 dias e até o término da internação. Os homens (86,9%) e a faixa etária de 20 a 29 anos (36,0%) foram as mais freqüentes. Os atropelamentos (45,1%) e o envolvimento de motocicletas e seus ocupantes (30,9%) foram os destaques dentre os mecanismos de trauma. A média do RTS na cena e do ISS, foram respectivamente 8,8 e 19,4.Os segmentos corpóreos mais atingidos foram: cabeça (58,8%), membros inferiores (45,1%) e superfície externa (40%). A média de tempo consumido na fase de APH foi 41min (tempo de cena 20,2min). Ocorreram 36% de óbitos, (metade em até 6 horas). A análise estatística revelou 24 fatores associados à sobrevivência, dentre eles, os procedimentos respiratórios avançados e os circulatórios básicos, as variáveis relativas ao RTS e a gravidade (ISS, MAIS e o número de lesões). No modelo final de Cox, ter sido submetido a procedimentos respiratórios avançados, compressões torácicas, apresentar lesão abdominal e ISS>25, foi associado a maior risco para o óbito até 48h após o trauma. Até 7 dias, a compressão torácica não se manteve no modelo final e a PAS de zero a 75mmHg apresentou associação com a morte após o acidente. Até a alta hospitalar, a ausência de PAS na avaliação inicial permaneceu no modelo. A reposição de volume foi o único fator com valor protetor para o risco de óbito presente em todos os momentos / The prehospital care (PH) is an important resource to trauma victims’ care. Nevertheless, there is great difficulty in demonstrating the PH intervention’s positive effect in victim’s survival, especially when concerning the advanced life support (ALS). The aim of this study is to characterize motor vehicle crash victims with Revised Trauma Score (RTS) <11 cared by municipal ALS and moved to tertiary hospitals in São Paulo in addition to identifying the prehospital variables associated to survival, and to evaluate their values as victim survival outcome determinant. The variables evaluated were: sex, age, trauma mechanism, basic life support and ALS procedures, physiological measures in the accident scene (considering the RTS, its parameters and fluctuations), the time consumed in PH phase, trauma severity by Injury Severity Score (ISS), the Maximum Abbreviated Injury Scale (MAIS) and number of lesions in each body region. The main results obtained by 175 victims between 12 e 65 years of age were submitted to the Kaplan Meier Survival Analysis and to Cox Proportional hazards Regression Analysis. The dependent variable was the survival time after the motor vehicle accident considering the intervals up to 6,12,24 and 48hs , up to 7 days and until the time of hospital discharge. Men (86,9%) and the 20 to 29 aged group (36%) were the most frequent. The pedestrians struck by car (45,1%) and the motorcycles (and their riders) (30,9%)were the highlight in trauma mechanisms. The RTS and the ISS average were 8,8 and 19,4 respectively. The more damaged body regions were head (58,8%), lower limbs (45,1%) and external surface (40%).The prehospital time average was 41 min (scene time 20,2min).Death rate was 36% (half of which up to 6hs).The statistical analysis revealed 24 survival associated factors. The ALS and the circulatory basic procedures, the RTS variables and the trauma severity (ISS,MAIS and number of lesions) were within them. In the final Cox Model were associated to higher risk of death up to 48hs after trauma: the submission to ALS respiratory procedures, chest compressions, the presence of abdominal injuries and ISS>25 .Until the 7th day the chest compression was not sustained in a final model and the systolic blood pressure (SBP) from zero to 75mmHg revealed statistical association with death after trauma. Until hospital discharge the SBP absence in scene evaluation remained in the model. The prehospital intravenous fluid refilling was the only factor of protector value to death risk in all moments

Nesta dissertação é feita uma avaliação dos resultados da aplicação do modelo de previsão de acidentes apresentado no Highway Safety Manual - HSM, publicado pela American Association of State Highway and Transportation Officials (AASHTO) no ano de 2010, para o caso de trechos de rodovia de pista simples localizados no interior do estado de São Paulo. São analisados o método original do HSM, o método do HSM calibrado para os trechos de rodovias estudados e o método empírico de Bayes. Os resultados apresentados pelo método original do HSM são bastante distintos dos valores reais observados, o que exclui a possibilidade do seu emprego direto no universo analisado. No entanto, os valores resultantes da aplicação do método do HSM calibrado e do método de Bayes, em todas as análises realizadas, aproximam-se de maneira satisfatória dos valores observados (com resultados melhores no método de Bayes) - o que mostra que esses métodos podem ser utilizados para a previsão de acidentes no universo analisado, bem como em outras situações com condições similares. Ainda que seja recomendada a realização de estudos específicos para a aplicação do modelo em outras regiões do país, na ausência desses estudos, os valores obtidos neste trabalho podem ser empregados como primeira aproximação. / This research conducts an evaluation of the results achieved by means of the application of crash prediction method presented by the Highway Safety Manual - HSM, published by the American Association of State Highway and Transportation Officials (AASHTO) in 2010, for the case of two lane highway segments situated in the state of Sao Paulo. The analyses were aimed at the original method of the HSM, the method calibrated to the studied highways segments and with the use of the empirical Bayes method. The results obtained by application of the HSM original method are quite distinct from the actual crash values observed, which excludes the possibility of its direct employment in the universe analyzed. However, the values resulting from application of the calibrated HSM method and the method of Bayes, in all data analysis, approach satisfactorily the observed values (with better results with the use of Bayes method) - which shows that these methods can be used for the prediction of accidents in the universe analyzed, as well as in other situations with similar conditions. Although it is recommended to perform specific studies for the application of the method in other regions of the country, in the absence of these studies, the values provided by this research study can be used as a first approximation.

Roadway safety continues to be a priority for the Utah Department of Transportation (UDOT) Traffic and Safety Division. UDOT has participated in and managed several research projects in recent years to determine the roadway segments of highest safety concern in the state. This research has provided UDOT with more tools to assist in safety project prioritization. Researchers in Department of Civil and Environmental Engineering at Brigham Young University (BYU) have worked with UDOT and the Statistics Department at BYU to create two network screening statistical tools called the Utah Crash Prediction Model (UCPM) and the Utah Crash Severity Model (UCSM) to analyze roadway segment safety. The Roadway Safety Analysis Methodology (RSAM) was developed as a process to run these segment models. Because a significant portion of crashes occur at intersections, there is a need to analyze roadway safety specifically at intersections. This research focuses on the development of the Utah Intersection Crash Prediction Model (UICPM) and the Intersection Safety Analysis Methodology (ISAM). The UICPM is a Bayesian generalized linear model that determines crash distributions for each intersection based on roadway characteristics and historical crash data. The observed number of crashes at each intersection is compared with the crash distribution, and a percentile value is calculated as the probability that the number of crashes occurring at an intersection in a particular year is less than or equal to the average annual number of crashes. A high percentile value indicates that more crashes were observed than expected and the intersection is a hot spot and should be considered for safety improvements. All intersections are ranked at the state, UDOT Region, and county levels based on the percentile value, the higher ranks having higher percentile values. The ISAM is the three-step process that was developed to execute the UICPM. The first step is to prepare the model input by formatting and combining the roadway characteristics and crash data files. Crashes are assigned to intersections if they fall with the functional area of an intersection. Due to data limitations, the ISAM is currently being used only for intersections of at least two state routes. It is anticipated that, as more data are made available, the ISAM will function properly for intersections of non-state routes as well. The second step is to execute the UICPM using the R GUI tool and R software. The third step is to create a two-page Intersection Safety Analysis Report (ISAR) for intersections of interest and maps of the state, UDOT Regions, and counties with the model results. Parts of the ISARs are auto-generated and the rest is entered manually by an analyst. The two-page ISARs will be used by UDOT Regions to prioritize intersection safety projects in their respective areas.

The Utah Department of Transportation (UDOT) Traffic and Safety Division continues to advance the safety of the state roadway network through network screening and decision making tools. In an effort to aid UDOT in meeting this goal, the Department of Civil and Environmental Engineering at Brigham Young University (BYU) has worked with the Statistics Department in developing analysis tools for highway safety, specifically the Utah Crash Prediction Model (UCPM) and the Utah Crash Severity Model (UCSM). Additional tools and methodologies, such as the "Hot Spot Identification and Analysis," have been created to summarize the roadway characteristics, crash data, and possible countermeasures of roadway segments with safety problems.This research focuses on the creation of a three part "Roadway Safety Analysis" methodology, which applies and automates the cumulative work of recently completed highway safety research conducted for UDOT. The first part is to prepare the roadway data and crash data for the statistical analysis. The second part is to perform the network screening statistical analysis; rank the segments by state, UDOT Region, and county; and select segments of interest. The third part is to compile and publish the Roadway Safety Analysis reports for the selected segments of interest. These parts are accomplished using the automation tools and graphical user interfaces (GUIs), which are documented in three respective volumes of user manuals. The automation tools and GUIs were developed with checks and processes to allow the Roadway Safety Analysis methodology to be completed with new, updated roadway and crash datasets.The Roadway Safety Analysis methodology allows future iterations of the UCPM and UCSM analysis and compilation of the Roadway Safety Analysis reports to be conducted in a user friendly environment. A series of critical data columns were identified to communicate the need for data consistency for future iterations of this safety research. An example of the entire process of the Roadway Safety Analysis methodology is given to illustrate how the three parts tie together. The overall process has automated data processing tasks, which saves time and resources for the analyst to investigate possible safety measures for segments of interest. Recommendations for future highway safety research are given, including continued development of the Roadway Safety Analysis methodology, an analysis of intersections and horizontal curves, the implementation of the Roadway Safety Analysis methodology to other states, and the advancement of safety countermeasures and geospatial tools for highway safety research.

Pedestrians and bicyclists are the most vulnerable road users and suffer the most severe consequences when crashes take place. An extensive literature is available for crash severity in terms of driver safety, but fewer studies have explored non-motorized users' crash severity. Furthermore, most research efforts have examined pedestrian and bicyclist crash severity in urban areas. This study focuses on state roads (mostly outside major urban areas) and aims to identify contributing risk factors of fatal and severe crashes involving pedestrians and bicyclists in state roads. Two ordinal regression models were developed (one for pedestrian and the other for bicyclist crashes) to examine crash severity risk factors. Additional models were developed to investigate road and traffic characteristics that could increase the likelihood of fatal crashes. In the model for pedestrian crash severity risk factors such as age, vehicle type and movement, light conditions, road classification, traffic control device, posted speed limit, location of the pedestrian and wet road surface during clear weather conditions are statistically significant. The bicyclist crash severity model indicates that age, crash location, vehicle movement and alcohol intoxication during dark conditions are statistically significant. In terms of road characteristics and traffic conditions, the models suggested risk factors such as arterials, light conditions, posted speed limit, roadways, and high heavy vehicle volume, increased the odds of a crash being fatal. The results seem to suggest that besides improvements in roadway characteristics, additional countermeasures to reduce crash severity for vulnerable users should include separation of vulnerable users from traffic, educational campaigns, more strict control of alcohol intoxicated drivers, and protection strategies of senior pedestrians.

Road traffic deaths, which affect people in their productive years, are projected to be the third leading cause of death by the year 2030. While most studies have focused on road infrastructure and vehicle safety, this study examined something new: the impact of prehospital response to road traffic accidents on the rate of death. Some countries send physicians to the scene of an accident; some send paramedics or registered nurses. The question this research sought to answer was whether the use of physician responders resulted in a lower rate of death compared to the use of nonphysician responders. The literature makes it clear that rate of road traffic death is related to country income and governance indicators, so first those variables needed to be equalized. My conceptual framework for this cross-sectional correlation study was the Haddon matrix, which organizes injuries by temporal (pre-event, event, and postevent) and epidemiological (host, agent, and environment) factors. Using World Health Organization data on road traffic injury and country income, World Bank data on governance indicators, and a literature search of 67 countries' prehospital response profiles, significant negative correlations (p > 0.001) were found for road traffic deaths and income, r (65) = -0.68, and governance indicators, r (65) = -0.646. No significant difference in the rate of road traffic death was found between physician and nonphysician prehospital staffing. Because increasing countries' income and improving governance are long-term, ambitious goals for developing countries, training nonphysician prehospital responders appears to be the most effective social change to decrease the burden of road traffic deaths.

Contexte : il est possible qu’une victime subisse de multiples conséquences d’accident de la route,conséquences pouvant retentir durablement sur sa vie. Cependant, peu d’études permettent de connaitre leprofil du blessé grave ainsi que les facteurs prédictifs de son devenir. De plus, il existe peu d'outilsprédictifs servant à prédire les conséquences post-accidentelles. L’objectif de la thèse est de caractériserces conséquences, de chercher les éléments pronostiques de gravité des conséquences un an aprèsl’accident et de donner une évaluation, à partir de données réelles, de la qualité de prédiction del’indicateur de déficience à un an appelé IIS (Injury Impairment Score - un indice de déficience - défini apriori à partir des lésions- et utilisé fréquemment).Méthodes : la thèse est réalisée dans le cadre de la cohorte ESPARR (Étude et Suivi d’une Populationd’Accidentés de la Route dans le Rhône), qui s’appuie sur les données du Registre des accidents de lacirculation du Rhône, et qui inclut 1372 sujets blessés dans des accidents de la route dont 1168 sujets âgésde 16 ans et plus. Parmi ces sujets, 886 adultes ont répondu à un questionnaire de suivi à un an, 616 sujetsont des données complètes et sont classés dans des groupes homogènes en fonction de leur devenir à unan par l'analyse des correspondances multiples et la méthode de classification hiérarchique. L’analyse desfacteurs prédictifs de leur appartenance à un de ces groupes de victimes, mesurés à la date de l'accident, aété effectuée à l’aide de modèles de régressions logistiques multinomiales pondérés. L'évaluation de l'IISsur les données réelles est réalisée en regardant la cohérence entre l'IIS et les différents facteurs mesurés àun an.Résultats : cinq groupes homogènes au niveau des conséquences de l’accident à un an ont été identifiés :le groupe-1 contient 206 sujets, dont une majorité est considérée en bonne récupération ; le groupe-2concerne les sujets ayant uniquement des conséquences physiques ; les groupes 3, 4 et 5 concernent lessujets ayant des conséquences multiples. À part les conséquences physiques en lien avec les sujets dansces groupes, certains plus en lien avec des répercussions sur la vie social (groupe-3), d’autres en lien avecdes difficultés sociales ou environnementales (groupe-4). Le groupe-5 comprend tous les sujets quisouffrent de syndrome post-commotionnel de la population d’étude. Après avoir ajusté sur plusieursvariables recueillies lors de l'accident, notre étude montre que, en plus des facteurs déjà évoqués dans lalittérature (âge, gravité…), le niveau de fragilité socioéconomique et le fait d'avoir un proche blessé dansl'accident sont également des facteurs prédisant le devenir des victimes d’un accident. En ce qui concernel'évaluation de l'IIS sur les données réelles, nous trouvons que le niveau des conséquences prédites par l’IIS ne correspond pas parfaitement à celui observé en réalité à un an quels que soient les facteurs mesurés.Conclusion : un an après l’accident, de nombreuses victimes d'accident de la route, même parmi cellessouffrant de lésions légères, continuent de présenter de multiples problèmes tant sur leur santé physiqueque mentale, sur le plan social ainsi que sur leur environnement. Dans une perspective de réadaptation à lavie quotidienne, ces résultats peuvent être utiles à l’amélioration de la prise en charge des accidentés de laroute. / Background: it is possible that victims can suffer from multiple problems after an accident, and this canbe seen in the people with the most serious consequences. However, few studies allow us to know theprofile and prognostic factors of severity of consequences after the accident in this population of victims.Moreover, there are few tools to predict 1-year post-traumatic sequelae in road crash victims.The thesis aims to determine subgroups of victims with similar outcomes 1 year after the crash andpredictive factors for attribution to these subgroups and validate sequelae prediction by the InjuryImpairment Score (IIS), in comparison with the one year outcomes.Methods: the thesis is a part of the broader ESPARR study based on the Rhône Registry of Road TrafficCasualties. The ESPARR cohort comprised 1,372 subjects, including 1,168 aged 16 years. Among 886adult subjects who responded to a follow-up questionnaire one year later, the main analysis was carriedout on 616 participants, who completed a self-report questionnaire on health, social, emotional andfinancial status 1 year after a crash. The multiple correspondence analysis and hierarchical clusteringmethod was implemented to produce homogeneous road-crash victim subgroups according to differencesin outcome. Baseline (time of accident) predictive factors for subgroup attribution were analysed onweighted multinomial logistic regression models. We used outcomes data at 1-year follow-up of roadinjury to validate the ability of IIS to predict sequelae.Results: five different victim groups were identified in terms of consequences one year after the crash:one group (206 subjects, 33.4%) presented few problems, one group with essentially physical sequelae,one group with essentially physical and social problems, and two groups presented many problems (oneincluded more victims with psychological problem and less environment problem). As well as the knownprognostic factors of age, initial injury severity and lesion type, socioeconomic fragility and the fact of arelative being involved in the accident emerged as being predictive of poor outcome one year later. IIS, inthis injured population, failed to predict sequelae one year later as measured by real data.Conclusion: one year after a road accident, victims may still experience multiple problems in terms notonly of physical health but also of mental health, social life and environment. Poor outcome may bepredicted both from accident-related factors and from victims' socioeconomic fragility. These findings areuseful in guiding prevention in terms not only of recovery of health status but also of recovery of sociallife in the best possible environment.

La présence de distorsions inévitables fait que les méthodes classiques de réduction d'échelle<br />sont inexploitables pour la prédiction du comportement non-linéaire de structures en<br />composite stratifié. Dans un premier temps, une nouvelle méthode capable de tenir compte<br />des effets d'échelle est développée en s'appuyant sur l'exemple d'absorbeurs d'énergie en<br />verre E / époxy sollicités en compression axiale statique. Dans un second temps, une étude<br />fréquentielle est réalisée de façon à étendre cette méthode aux sollicitations en dynamique<br />rapide. Des comparaisons avec les résultats issus de la similitude de Cauchy mettent en<br />évidence un gain important en terme de précision des prédictions des paliers d'effort. Enfin,<br />une modélisation par éléments finis est réalisée afin d'étudier les différents phénomènes qui<br />se produisent lors du crash et de tester l'utilisation de la similitude indirecte. Ce modèle<br />numérique permet de préciser les causes de l'effet d'échelle détecté précédemment.