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Abstract: Road traffic accidents claim more than 1,500 lives each year in Canada and affect society adversely, so transport authorities must reduce their impact. This is a major concern in Quebec, where the traffic-accident risks increase year by year proportionally to provincial population growth. In reality, the occurrence of traffic crashes is rarely random in space-time; they tend to cluster in specific areas such as intersections, ramps, and work zones. Moreover, weather stands out as an environmental risk factor that affects the crash rate. Therefore, traffic-safety engineers need to accurately identify the location and time of traffic accidents. The occurrence of such accidents actually is determined by some important factors, including traffic volume, weather conditions, and geometric design. This study aimed at identifying hotspot locations based on a historical crash data set and spatiotemporal patterns of traffic accidents with a view to improving road safety. This thesis proposes two new methods for identifying hotspot locations on a road network. The first method could be used to identify and rank hotspot locations in cases in which the value of traffic volume is available, while the second method is useful in cases in which the value of traffic volume is not. These methods were examined with three years of traffic-accident data (2011–2013) in Sherbrooke. The first method proposes a two-step integrated approach for identifying traffic-accident hotspots on a road network. The first step included a spatial-analysis method called network kernel-density estimation. The second step involved a network-screening method using the critical crash rate, which is described in the Highway Safety Manual. Once the traffic-accident density had been estimated using the network kernel-density estimation method, the selected potential hotspot locations were then tested with the critical-crash-rate method. The second method offers an integrated approach to analyzing spatial and temporal (spatiotemporal) patterns of traffic accidents and organizes them according to their level of significance. The spatiotemporal seasonal patterns of traffic accidents were analyzed using the kernel-density estimation; it was then applied as the attribute for a significance test using the local Moran’s I index value. The results of the first method demonstrated that over 90% of hotspot locations in Sherbrooke were located at intersections and in a downtown area with significant conflicts between road users. It also showed that signalized intersections were more dangerous than unsignalized ones; over half (58%) of the hotspot locations were located at four-leg signalized intersections. The results of the second method show that crash patterns varied according to season and during certain time periods. Total seasonal patterns revealed denser trends and patterns during the summer, fall, and winter, then a steady trend and pattern during the spring. Our findings also illustrated that crash patterns that applied accident severity were denser than the results that only involved the observed crash counts. The results clearly show that the proposed methods could assist transport authorities in quickly identifying the most hazardous sites in a road network, prioritizing hotspot locations in a decreasing order more efficiently, and assessing the relationship between traffic accidents and seasons. / Les accidents de la route sont responsables de plus de 1500 décès par année au Canada et ont des effets néfastes sur la société. Aux yeux des autorités en transport, il devient impératif d’en réduire les impacts. Il s’agit d’une préoccupation majeure au Québec depuis que les risques d’accidents augmentent chaque année au rythme de la population. En réalité, les accidents routiers se produisent rarement de façon aléatoire dans l’espace-temps. Ils surviennent généralement à des endroits spécifiques notamment aux intersections, dans les bretelles d’accès, sur les chantiers routiers, etc. De plus, les conditions climatiques associées aux saisons constituent l’un des facteurs environnementaux à risque affectant les taux d’accidents. Par conséquent, il devient impératif pour les ingénieurs en sécurité routière de localiser ces accidents de façon plus précise dans le temps (moment) et dans l’espace (endroit). Cependant, les accidents routiers sont influencés par d’importants facteurs comme le volume de circulation, les conditions climatiques, la géométrie de la route, etc. Le but de cette étude consiste donc à identifier les points chauds au moyen d’un historique des données d’accidents et de leurs répartitions spatiotemporelles en vue d’améliorer la sécurité routière. Cette thèse propose deux nouvelles méthodes permettant d’identifier les points chauds à l’intérieur d’un réseau routier. La première méthode peut être utilisée afin d’identifier et de prioriser les points chauds dans les cas où les données sur le volume de circulation sont disponibles alors que la deuxième méthode est utile dans les cas où ces informations sont absentes. Ces méthodes ont été conçues en utilisant des données d’accidents sur trois ans (2011-2013) survenus à Sherbrooke. La première méthode propose une approche intégrée en deux étapes afin d’identifier les points chauds au sein du réseau routier. La première étape s’appuie sur une méthode d’analyse spatiale connue sous le nom d’estimation par noyau. La deuxième étape repose sur une méthode de balayage du réseau routier en utilisant les taux critiques d’accidents, une démarche éprouvée et décrite dans le manuel de sécurité routière. Lorsque la densité des accidents routiers a été calculée au moyen de l’estimation par noyau, les points chauds potentiels sont ensuite testés à l’aide des taux critiques. La seconde méthode propose une approche intégrée destinée à analyser les distributions spatiales et temporelles des accidents et à les classer selon leur niveau de signification. La répartition des accidents selon les saisons a été analysée à l’aide de l’estimation par noyau, puis ces valeurs ont été assignées comme attributs dans le test de signification de Moran. Les résultats de la première méthode démontrent que plus de 90 % des points chauds à Sherbrooke sont concentrés aux intersections et au centre-ville où les conflits entre les usagers de la route sont élevés. Ils révèlent aussi que les intersections contrôlées sont plus à risque par comparaison aux intersections non contrôlées et que plus de la moitié des points chauds (58 %) sont situés aux intersections à quatre branches (en croix). Les résultats de la deuxième méthode montrent que les distributions d’accidents varient selon les saisons et à certains moments de l’année. Les répartitions saisonnières montrent des tendances à la densification durant l’été, l’automne et l’hiver alors que les distributions sont plus dispersées au cours du printemps. Nos observations indiquent aussi que les répartitions ayant considéré la sévérité des accidents sont plus denses que les résultats ayant recours au simple cumul des accidents. Les résultats démontrent clairement que les méthodes proposées peuvent: premièrement, aider les autorités en transport en identifiant rapidement les sites les plus à risque à l’intérieur du réseau routier; deuxièmement, prioriser les points chauds en ordre décroissant plus efficacement et de manière significative; troisièmement, estimer l’interrelation entre les accidents routiers et les saisons.

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Die Überlebenswahrscheinlichkeit der Unfallopfer nach Straßenverkehrsunfällen hängt von der Zeitspanne vom Unfall bis zur ersten suffizienten Hilfeleistung (therapiefreies Intervall) sowie von der Qualität der Erstversorgung ab. Das therapiefreie Intervall kann durch automatische Notrufsysteme (ACN) und suffiziente Laienhilfe verkürzt werden. In dieser Dissertation werden (1) Modelle zur Prognose der Verletzungsschwere von Fahrzeuginsassen für den Einsatz in erweiterten automatischen Notrufsystemen (AACN) entwickelt und (2) Anforderungen an Telemedizinsysteme zur Unterstützung von Laien bei der Durchführung von Erste-Hilfe-Maßnahmen untersucht. (1) Die Prognose der Verletzungsschwere ist für eine optimale Disposition der Rettungsmittel erforderlich. Auf der Basis der amerikanischen Unfalldatenbank NASS/ CDS und der deutschen Unfalldatenbank GIDAS werden Prognosemodelle mit multivariaten inferenzstatistischen Verfahren (decision tree, logistic regression) entwickelt, die Bedeutung einzelner Eingangsgrößen untersucht und die Leistungsfähigkeit der Modelle überprüft. Die Leistungsfähigkeit beider statistischen Verfahren stellt sich in ROC-Analysen als vergleichbar heraus. Mit den Prognosemodellen kann eine Dispositionsempfehlung erstellt werden, die heutigen Dispositionsentscheidungen auf der Grundlage eines Telefongesprächs mit dem Unfallmelder qualitativ entspricht. (2) Zur Entwicklung eines Telemedizinsystems für die Laienunterstützung wird untersucht, ob die telemedizinische Anleitung von Laien bei der Durchführung von Erste-Hilfe-Maßnahmen zu einer Erhöhung der Hilfsbereitschaft führt und welche Anforderungen ein Telemedizinsystem erfüllen muss. Dazu werden die am häufigsten indizierten Erste-Hilfe-Maßnahmen nach Verkehrsunfällen durch Auswertung der GIDAS-Datenbank identifiziert, der Stand der heutigen Laienhilfe analysiert, die erforderlichen Funktionen eines Telemedizinsystems abgeleitet und der Einfluss einer verbesserten Laienhilfe auf die Überlebenswahrscheinlichkeit bestimmt. / The probability of survival of motor vehicle accident victims depends on two factors: the time interval between the accident and the initial provision of appropriate first-aid (therapy-free interval), and the quality of the first-aid treatment. The therapy-free interval can be shortened significantly by automatic crash notification systems (ACN) and by adequate bystander first aid. In this thesis, (1) models are developed for predicting the severity of injury of vehicle occupants for use in advanced automatic crash notification systems (AACN) and (2) requirements of telemedical bystander support systems are examined. (1) The prediction of the severity of injury is needed for optimal disposition of rescue services. Therefore, prediction models are developed on the basis of the American accident database NASS/ CDS and its German counterpart, GIDAS, using multivariate inference statistical procedures (decision tree, logistic regression). In addition, the importance of individual parameters and the efficiency of these models are investigated. The performance of the two statistical procedures proves to be equal by using the ROC analyses. The prediction models allow for recommendations of rescue services that correspond in quality to contemporary dispatching decisions for rescue services on the basis of a telephone call between the individual reporting the accident and a dispatcher. (2) Concerning the development of a telemedical bystander support system, the paper examines whether the availability of telemedical guidance leads to an increase in bystander willingness to provide first aid. In order to evaluate the requirements of a telemedical system, the most frequently indicated first-aid measures after traffic accidents are identified by evaluating the GIDAS database. Furthermore, the status of assistance currently offered by bystanders is analyzed, the necessary functions of a telemedical system are scrutinized, and the influence of improved bystander assistance on the probability of accident victims’ survival is determined.

Could shareholder primacy, with its assumed short-termist practices, have had its day when it comes to managerial activity centered on creating corporate value? Many business and opinion leaders appear to take this position, not least Jack Welch who famously declared 'shareholder primacy is the dumbest idea in the world!' Indeed, in a post-Crash economy has a wider stakeholder focus with a longer-term outlook superseded any business notions of shareholder primacy and wealth maximization? This research examines these possibilities through a consideration of the narrative companies produce, such as annual reports. From this corpus material, an assessment is made of whether UK managers' perceptions about corporate value generation changed over the period covering the worldwide financial crisis, with respect to their relative favouring of shareholders and stakeholders. The corpus of narrative material used is visualized as a conceptual space in which a conversation reflecting perceptual bias to the generation of corporate value occurs. To explore such corpuses, in order to compare narratives at points either side of the 2008 Crash, a new methodology was devised called narrative staining. Hence, a detection and visual mapping over the period was made possible of managers' changing perceptions concerning primacy (shareholder or stakeholder orientation) with its mediation by termism (a short or long-term bias). Termism is also originally conceived as part of a larger temporal category, which includes a sense of urgency to act (urgent versus non-urgent) that is similarly examined. The investigation reveals that over time perceptual change about value creation happened, though in unanticipated ways. Companies pre-Crash were often short-term stakeholder oriented then moved post-Crash to a long-term shareholder orientation. A focus for this study was the corporate domain, consisting of a selection of FT250 companies. However, managerial perceptions about corporate value creation are influenced not simply by the conversation of the corporate domain but rather by a multi-actor conversation taking place throughout the business environment. To comprehend this effect, the research mines further corpuses that comprise the UK's regulatory domain (hard and soft law), the press (Financial Times and other newspapers), and relevant peripheral stakeholder organizations (including the Confederation of British Industry, the Institute of Directors, and the Trades Union Congress). These organizations demonstrated more complex, unforeseen, perceptual effects as the financial crisis proceeded with many aligning according to their political or business agenda, which also impacted any sense of urgency to act they had. There appears to be no previous attempt at an extensive and multivariate analysis of this nature. And the findings challenge prevalent characterizations of shareholder and stakeholder behaviour. Moreover, the research shows that utilizing a wide set of stakeholder corpuses acts a viable proxy for broader financial perspectives amongst UK organizations. The technique of narrative staining therefore provides insights, hitherto inaccessible, for assessing and consolidating large-scale perceptual bias regarding value creation across the economy. The technique also has significant potential for other applications.

Man-made materials such as fiber-reinforced composites (FRCs) can be tailored for optimum performance in product design applications in terms of strength and weight. The current work is aimed at studying the behaviors of composite laminates based on E-glass CSM (Chopped Strand Mat) or WRM (Woven Roving Mat) plies with a polyester resin for impact protection applications. Detailed mechanical characterization of CSM and WRM laminates till failure is carried out for tensile, compressive and shear loads by varying manufacturing process, number of plies, and laminate thickness. The effect of fiber volume fraction on mechanical properties is shown. The efficacy of CSM and WRM laminates as energy- absorbing countermeasures is studied by performing quasi-static and axial impact tests on cylindrical tubes made of the stated FRCs. In addition to load-displacement and specific energy absorption attributes, failure modes are of interest in such studies. The potential of FRC laminates for protection against projectile impact is investigated by performing low velocity impact perforation tests with a falling tup fitted with an indentor, and medium to high velocity projectile impact tests in a gas gun-based device. The valuable results generated are used for the validation of nonlinear finite element-based CAE (Computer-Aided Engineering) procedures including application of a multi-modal failure criterion for explicit dynamic analysis. The present study not only throws light on complex mechanical behavior of an important class of lightweight materials under static and dynamic loads, but also simulation tools for the design of impact safety countermeasures such as bullet-proof laminates and energy–absorbing components for automotive body structures.

Network screening and countermeasure selection are two crucial steps in the highway improvement process. In network screening, potential improvement locations are ranked and prioritized based on a specific method with a set of criteria. The most common practice by transportation agencies has been to use a simple scoring method, which, in general, weighs and scores each criterion and then ranks the locations based on their relative overall scoring. The method does not deal well with criteria that are qualitative in nature, nor does it account for the impacts of correlation among the criteria. The introduction of Analytic Hierarchy Process (AHP) provides agencies with a method to include both quantitative and qualitative criteria. However, it does not address the issue on correlation. This dissertation explores the use of both Analytic Network Process (ANP) and Fuzzy Analytic Network Process (FANP) for their potential capabilities to address both issues. Using urban four-lane divided highways in Florida for bicycle safety improvements, both ANP and FANP were shown to provide more reasonable rankings than AHP, with FANP providing the best results among the methods. After the locations are ranked and prioritized for improvements, the next step is to evaluate the potential countermeasures for improvements at the selected top-ranked locations. In this step, the standard practice has been to use Crash Modification Factors (CMFs) to quantify the potential impacts from implementing specific countermeasures. In this research, CMFs for bicycle crashes on urban facilities in Florida were developed using the Generalized Linear Model approach with a Zero-Inflated Negative Binomial (ZINB) distribution. The CMFs were tested for their spatial and temporal transferability and the results show only limited transferability both spatially and temporally. The CMFs show that, in general, wider lanes, lower speed limits, and presence of vegetation in the median reduce bicycle crashes, while presence of sidewalk and sidewalk barrier increase bicycle crashes. The research further considered bicycle exposure using the bicycle activity data from the Strava smartphone application. It was found that increased bicycle activity reduces bicycle crash probabilities on segments but increases bicycle crash probabilities at signalized intersections. Also, presence of bus stops and use of permissive signal phasing at intersections were found to increase bicycle crash probabilities.

Generation Z har under sin korta tid som investerare på den finansiella marknaden varit med om en säregen börskrasch till följd av coronapandemin 2020. Börskraschen 2020 var unik i förhållande till tidigare börskrascher såsom IT-kraschen 2000 och finanskrisen 2008 eftersom marknaden återhämtade sig och nådde nya rekordnivåer inom ett halvår. Samtidigt stod svenska investerare under de första månaderna av 2022 inför ett nytt ras där den genomsnittliga aktien på Stockholmsbörsen sjunkit med ungefär 36% från dess högsta nivå under perioden 2020–2022 till följd av en hög inflationstakt samt Rysslands invasion av Ukraina. Forskningen kring den yngsta gruppen investerare, generation Z, som saknar erfarenhet av långvariga osäkra marknadsförhållanden är bristfällig och ger därmed upphov till en ny grupp investerare att studera. Studiens syfte är att studera hur riskbenägenhet samvarierar med börspsykologiska bias, kognitiv reflektionsförmåga och erfarenhet från tidigare finansiella kriser samt hur dessa faktorer skiljer sig mellan generation Z och tidigare generationer. Studien finner att generation Z till större del faller för samtliga börspsykologiska bias förutom överreaktion och visar på ett flertal signifikanta skillnader mellan generation Z och äldre generationer. Resultatet visar även att anchoring och konfirmeringsbiassamvarierar signifikant med riskbenägenhet och att den största skillnaden mellan generation Z och äldre generationer kan hänföras till börspsykologiska bias. / Generation Z has during their short time as investors experienced a market crash due to the covid-pandemic in 2020 but also a quick recovery in the same year where the market reached a new all-time high. The market crash in 2020 was unique compared to the crash following the burst of the Dot-com bubble in 2000 and the financial crisis in 2008 because of the quick recovery of the stock market that led to new all-time highs. However, during the first months of 2022, Swedish investors were once again experiencing a market crash where the average stock on the Stockholm stock exchange had lost more than 36% of its value since their peak between 2020-2022 due to high inflation and Russia’s invasion of Ukraine. The youngest group of investors, generation Z, lacks experience from long-lasting uncertainties in the stock market. Research regarding generation Z is insufficient which gives rise to a new group of investors to study. The purpose of the thesis is to study the relationship between risk tolerance and psychological biases, cognitive reflection and experience from previous stock market crashes and how these factors differ between generation Z and older generations. The thesis finds that generation Z is indicated to be more affected by every psychological bias except overreaction and finds several significant differences between generation Z and the older generations. The result also shows that confirmation bias and anchoring have a significant relationship to risk tolerance and that the largest differences between generation Z and older generations are derived from psychological biases.