Thesis--Helsinki University, 1989. / Includes bibliographical references (p. 50-55).

Tubes of glass reinforced thermosetting resins have been tested in axial compression between steel platens with one end chamfered to prevent critically high loads causing catastrophic centre failure. By testing in such a manner these tubes crush in a progressive and controlled manner, and are capable of exhibiting high levels of energy absorption, particularly when related to the material mass involved. Polymers are known to display viscoelastic behaviour and polymer composites are similarly sensitive to test speed and temperature. Energy absorption in tube crushing has been shown to be speed and temperature sensitive and the purpose of this project has been to understand the variability of the energy absorption and the associated mechanisms. The main aim has been to show how the two variables interrelate. The materials used have been produced by hot rolling of pre-preg cloth or by resinjection into closed moulds. Reinforcement has consisted of woven glass cloth or random glass mat; matrix materials have been epoxy and polyester resins. Trends to higher values of specific energy absorption with increasing speed have been observed for epoxy matrix tubes, while polyester matrix tubes have shown less certain trends and give lower values of specific energy absorption at high speeds. All the tubes have shown a rapid drop in specific energy absorption with increasing temperature above normal room temperature, with changes in crush mode being very apparent. At temperatures in excess of about 100 degrees C the tubes have failed by centre buckling, the transition temperature from normal crushing to buckling being sensitive to the crush speed. The interrelation between speed and temperature effects has been examined. Three factors that prevent simple interrelation have been identified; these are inertial effects of crush debris, residual stresses in the hoop direction of the tube and frictional heating in the crush zone. Speed sensitivity of the energy absorption has been determined over a range of temperatures and various features of these responses related to the responses of the material properties. Frictional temperature rises have been modelled mathematically and the predictions have been shown to be reasonably consistent with experimental measurements. These temperature rises have been shown to be important in determining the speed sensitive behaviour of the energy absorption levels, particularly for polyester resin matrix tubes tested at high speeds.

In North America, the last two decades saw continued increases in population multimorbidity across all age groups. This trend, which is expected to endure in the coming years, has been attributed in large part to population aging and unhealthy lifestyle choices. While the societal consequences of multimorbidity have focused primarily on the burden it imposes on the sustainability of health systems and the need to implement innovative ways to deliver care, latent costs, such as possible increases in motor-vehicle accidents (MVAs) have received relatively little attention. The principal objective of this thesis was to investigate the relationship between multimorbidity and MVAs. To complement current knowledge on the topic, we conducted observational studies based on information recorded in electronic health records (EHR). The hypothesis that increasing levels of multimorbidity would translate into increasing risk of MVA was tested in both a general population of health care recipients and in persons with epilepsy, a subgroup of individuals predisposed to comorbidities and MVAs. To gain a better understanding of morbidity ascertainment in EHR data, preliminary validation studies were performed to evaluate the performance of Elixhauser comorbidity measures for predicting hospital mortality in our data source. A systematic review of risk factors contributing to the onset and progression of epilepsy was also performed in hopes of identifying elements that would help improve the methodological design of the principal thesis study limited to persons with epilepsy. Study results confirmed the excellent performance of the Elixhauser comorbidity measures for predicting hospital mortality in the Cerner Health Facts data repository. In the general health care recipient population, a positive exposure-outcome relationship was observed between multimorbidity and MVA risk. This relationship was consistent in adults across the lifespan and more pronounced in women than in men. In persons with epilepsy, the observed exposure-outcome relationship between multimorbidity and MVAs did not reach statistical significance. However, comorbid depression was identified as a risk factor for MVAs. Given increasing rates of multimorbidity in the general population, the findings of this thesis strongly support the need for replication and better characterization of the disease combinations that drive increases in MVA risk. Future work on this topic should also include estimates of MVA risk attributable to multimorbidity; this would inform and gauge the relevance of novel driving policies targeting individuals diagnosed with specific health conditions.

Préserver l’intégrité des occupants d’un véhicule lors d’un accident constitue un enjeu majeur pour les constructeurs automobiles depuis de nombreuses années. L’objectif de cette thèse est d’analyser l’effet de la pré-déformation plastique sur la tenue au crash d’une structure de type crash-box. L’histoire du chargement est composée de deux phases. La première est le processus de mise en forme qui est généralement réalisé sous chargement quasi-statique. La seconde phase est caractérisée par un évènement de type crash. Le comportement de trois aciers fréquemment utilisés dans l’industrie automobile a été étudié (BH260, DP600, TRIP800). Des essais en traction uni-axiale ont permis de mettre en évidence l’effet d’un pré-chargement quasi-statique sur la réponse en rechargement dynamique. Une large campagne expérimentale d’écrasement de structures a par ailleurs révélé que le processus de pré-déformation a un effet bénéfique sur la tenue au crash malgré la réduction de l’épaisseur des structures. Deux modèles phénoménologiques sont ensuite proposés pour décrire les effets d’écrouissage et de sensibilité à la vitesse de déformation des métaux. Les prédictions des modèles montrent une très bonne correspondance avec les données expérimentales dans une large gamme de vitesse de déformation et les effets d’histoire de vitesse de déformation peuvent être très bien pris en compte par l’un des modèles. Enfin, une démarche numérique de couplage emboutissage-crash est présentée où les variables calculées lors de la mise en forme (contraintes résiduelles, déformation plastique équivalente, épaisseur finale) sont prises en compte lors de l’écrasement sous chargement dynamique / To preserve the integrity of vehicle passengers during a crash constitutes a major goal for the automotive manufacturers since many years. The aim of this Ph-D thesis is to analyze the effect of a plastic prestrain on crash properties of a crash-box structure. The loading history is composed of at least two phases. The first phase is the forming process, in general under quasi-static conditions. The subsequent loading is due to a crash event. The behavior of three steels frequently used in the automotive industry has been studied (BH260, DP600, TRIP800). The experimental characterization of the steels shows the effect of a quasi-static prestrain on subsequent dynamic tensile curves. In addition, a large experimental crushing campaign of structures revealed that the prestrain process improves the crash behavior despite a reduction of the wall thickness. Two phenomenological models are then proposed to describe the strain-hardening effects and strain-rate sensitivity of metals. The model predictions show a very good agreement with experimental results for a wide range of strain-rate. Strain-rate history effects are well accounted for by one of the models. Finally, a numerical approach is performed where the variables calculated during the stamping (residual stress, equivalent plastic deformation, final thickness) are taken into account during the crash simulation under dynamic loading

Thesis deals with comparison of influence of chosen solution method on pre crash movement of vehicles in one simulation program and on differences between calculations for one method in different programs. Compared solution methods are kinematics and dynamics solutions of pre crash movement, compared programs are Virtual CRASH and PC-Crash.

Pedal misapplication (PM) is an error in which a driver unintentionally presses the wrong pedal. When drivers mistake the accelerator pedal for the brake pedal, the vehicle experiences a sudden unintended acceleration, and the consequences can be severe. A brief history of PM is covered, and several novel studies of PM are described. The goals of these studies were as follows: 1. Identify and analyze multiple samples of PM crashes from a variety of data sources using both established and novel methods to gain new insight into the characteristics and frequency of PM crashes. 2. Use the confirmed, real-world PM crash data to develop a custom vehicle dynamics simulation and evaluate the overall potential safety benefit of a theoretical PM advanced driver assistance system. Using an established keyword search identification method and two unique crash datasets, a PM crash frequency of approximately 0.2% of all crashes was found. These PM crashes were typically rear-end or road departure crashes in moderate- to low-speed commercial or residential areas. Female drivers and elderly drivers were more often involved in these PM crashes, which generally featured slightly lower injury severities and often involved inattention or fatigue. Anecdotally, PM crash narratives contained repeated evidence of unexpected events, driver inexperience, distraction, shoe-malfunction, extreme stress, and medical conditions/emergencies. A novel PM crash identification algorithm was developed to detect PMs from time-series pre-crash data. This algorithm was applied to a sample of crashes with event data recorder data available, and a frequency of 4.3% of eligible crashes were found to have exhibited PM behavior, suggesting that PM crashes may be more prevalent than previously thought. While the data from these crashes suggested that a PM occurred, this dataset lacked sufficient data regarding driver intention, which is necessary to confirm each crash as PMs. The characteristics of these PM-like crashes were analyzed and found to be largely similar to those of previous samples, with notable exceptions for higher proportions of male drivers, higher travel speeds, and higher maximum injury severities. More robust data from a naturalistic driving study (NDS) was acquired, and the novel algorithm was applied to all of the sample’s eligible crashes. Because the NDS data contained more data elements such as driver-facing video, crashes that exhibited PM behavior were individually inspected to confirm PM. This produced a PM crash frequency of 1.1%. The characteristics of these confirmed PM crashes were investigated, but a small sample size limits the generalizability of the results. Lastly, crash data from confirmed, real-world PM crashes was used to inform a custom vehicle dynamics model into which a theoretical PM advanced driver assistance system was simulated. The effect of the accelerator suppression system on crash avoidance and mitigation was evaluated to assess its potential safety benefit, which was found to be highly dependent on system threshold values and largely underwhelming in the absence of supplemental braking. The results indicated that a system that detected PM, suppressed acceleration, and applied braking could provide a substantially higher safety benefit. / M.S. / Pedal misapplication (PM) occurs when a driver presses the wrong pedal. When drivers mistake the accelerator pedal for the brake pedal, the vehicle experiences a sudden unintended acceleration, and the consequences can be severe. A history of the controversial subject of PM is covered, and several novel studies of PM are described. In these studies, PM crashes are identified among documented real-world crashes. This is done in three phases: (1) using narratives written by law-enforcement officers or crash investigators, (2) using event data recorders, or “black boxes,” that store vehicle data prior to crashes, and (3) using naturalistic driving study data, including video recordings of subjects during daily driving. These data are analyzed to develop the understanding of how often PM crashes occur and what factors are common among them. It is discovered that the frequency of PM crashes may be an order of magnitude greater than previously estimated. In the final study, real-world PM crash data is used to virtually reconstruct PM crashes and apply an advanced driver assistance system designed to detect PM, suppress the accelerator input, and reduce the severity of the crash or prevent it altogether. By simulating a wide range of system variations, we develop a sense of the feasibility of such a system’s implementation and overall safety benefit.

No description available.

This dissertation performs a comprehensive analysis of the effect of different environmental, demographic and vehicle variables on the severity of two-vehicle crashes. The limitations associated with previous studies have been addressed by using a large crash database, properly defining the independent variables, using appropriate statistical models, and by considering the effect of factors normally unaccounted for such as crash type, impact speed, and weight or height incompatibilities between the two vehicles.The use of multinomial logit models at the individual occupant and crash levels provides the flexibility to evaluate variables that have opposing effects at different injury levels (such as airbags). Alternative formulations with interaction terms and with instrumental variables are included. An analysis of marginal probabilities and costs is also provided, which is particularly useful when discussing potential safety treatments with transportation officials, politicians and other decision makers.The findings from the different models are consistent and suggest that the type of crash has a great impact on severity. Age is the most significant demographic variable, with children and older occupants being least and most likely to be injured, respectively. Behavior also seems to be critical, as the use of seatbelts greatly decreases occupant injuries. Heavier vehicles increase the safety of its occupants but decrease the safety of occupants of the other vehicle. The effect of vehicle type is not as significant as weight, with the exception of pickups, which are both more crashworthy and more aggressive than passenger cars. Further research is needed on the effects of airbags and impaired driving, as the analyses conducted have been inconclusive.

Master of Science / Department of Civil Engineering / Sunanda Dissanayake / The percentage of the U.S. population aged 65 years or older is increasing rapidly. Statistics also show this age group was 14.9 percent of the population in 2015 and is expected to be 20.7 to 21.4 percent for the years 2030–2050. Kansas has similar statewide trends with its aging population. Therefore, identifying issues, concerns, and factors associated with severity of older-driver crashes in Kansas is necessary. The Kansas Crash Analysis and Reporting System (KCARS) database maintained by Kansas Department of Transportation was used in this study to identify older-driver crash characteristics, compare older drivers with all drivers, and develop crash severity models. According to KCARS data, older drivers were involved in more than one in five fatal injuries out of all drivers in Kansas from 2010 to 2014. When compared with all drivers, older drivers were overly represented in fatal and incapacitating injuries. The percentage of older-driver fatal injuries was more than the twice that of all drivers. When compared with all drivers, older drivers were involved more often in crashes at four-way intersections, on straight and level roads, in daylight hours, and at a stop or yield signs. An in-depth crash severity analysis was carried out for the older drivers involved in crashes. Three separate binary logistic regression models were developed for single-vehicle crashes where only the older driver was present (Model A), single-vehicle crashes involving an older driver with at least one passenger (Model B), and multi-vehicle crashes involving at least one older driver (Model C). From the crash severity analysis, it was found that left turns were significant in changing the crash severity for Model A, but it was not significant in model B, meaning that older drivers may be safer with passengers. For Model B, none of the passenger attributes were significant, though it was originally developed to identify passenger attributes. Gender of the older driver was not significant in any model. For all models, variables such as safety equipment use, crash location, weather conditions, driver ejected or trapped, and light conditions distinguished crash severity. Furthermore, for Model A, variables such as day of the week, speed, accident class, and maneuver, distinguished crash severity. Moreover, accident class, surface type, and vehicle type changed crash severity in Model B. Number of vehicles, speed, collision type, maneuver, and two-lane roads were significant in Model C. A road-user survey was also conducted to identify habits, needs, and concerns of Kansas' aging road users since it was not advisable to conclude safety factors solely on crash data. The probability of occurrence was calculated by taking the weighted average of answers to a question. Then a contingency table analysis was carried out to identify relationships among variables. For older drivers, seatbelt use as a driver had the highest probability of occurrence. Driving in heavy traffic, merging into traffic, moving away from traffic, and judging gaps were dependent on age group. Findings of this research gave an understanding of older-driver crashes and associated factors. Since more than 85 percent of crash contributory causes were related to drivers, driver awareness programs, driver licensing restrictions, providing public transportation, and law enforcement can be used as countermeasures. Accordingly, results of this study can be used to enhance older-driver safety and awareness programs.

In this thesis an incident prediction model is formulated and calibrated. The primary idea of the model developed is to correlate the expected number of crashes on any section of a freeway to a set of traffic stream characteristics, so that a reliable estimation of likelihood of crashes can be provided on a real-time basis. Traffic stream variables used as explanatory variables in this model are termed as “incident precursors”. The most promising incident precursors for the model formulation for this research were determined by reviewing past research. The statistical model employed is the categorical log-linear model with coefficient of speed variation and occupancy as the precursors. Peak-hour indicators and roadway-type indicators were additional categorical variables used in the model. The model was calibrated using historical loop detector data and crash reports, both of which were available from test beds in Austin, Texas. An examination of the calibrated model indicated that the model distinguished different levels of crash rate for different precursor values and hence could be a useful tool in estimating the likelihood of incidents for real-time freeway incident management systems.