Orientador: Antonio Celso Fonseca de Arruda / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-17T07:26:37Z (GMT). No. of bitstreams: 1 Hainoski_SandroCarlos_M.pdf: 5270264 bytes, checksum: 2f957f1df243cd0769220970df187013 (MD5) Previous issue date: 2010 / Resumo: Foi objetivo deste trabalho, construir equipamentos que permitam a realização de alguns ensaios exigidos pela norma brasileira ABNT NBR 14.400. O conjunto de equipamentos selecionados, projetados e construídos, além de ensaiar alguns itens da norma, permitiu medir a tensão entre as pernas do ocupante de uma cadeirinha em condições dinâmicas de rotação. Tal medição possibilitou realizar pesquisa original e que tem significado nos casos de colisão com capotamento. Os equipamentos projetados e construídos foram: o ciclador, o dispositivo de capotamento e o boneco antropomórfico. Os ensaios realizados evidenciaram o ótimo desempenho dos equipamentos para as finalidades propostas. O trabalho possibilitou avaliar dois fechos e o desempenho ergonômico de três diferentes modelos de cadeirinhas relativo às tensões geradas entre as pernas e as tiras, em casos de capotamento / Abstract: This study aimed, to build equipment that allows the realization of some tests required by the Brazilian standard ABNT NBR 14400. The set of selected equipment, designed and built, In addition to rehearse some of the standard items, allowed measuring the tension between the legs of the occupant of a seat in the dynamic conditions of rotation. This measure is meaningful in cases of collision with rollover. The equipment was designed and built: the cycler, the overturning device and an anthropomorphic dummy. The tests showed the excellent performance of equipment for the purposes proposed. The study allowed evaluating two locks models and ergonomic performance of three different models of car seats on the tensions generated between the legs, the straps in case of rollover / Mestrado / Materiais e Processos de Fabricação / Mestre em Engenharia Mecânica

Driver distraction remains a matter of concern throughout the world as the number of car accidents caused by distracted driving is still unacceptably high. Industry and academia are working intensively to design new techniques that will address all types of driver distraction including visual, manual, auditory and cognitive distraction. This research focuses on an existing technology, namely in-car communication systems (ICCS). ICCS allow drivers to interact with their mobile phones without touching or looking at them. Previous research suggests that ICCS have reduced visual and manual distraction. Two problems were identified in this research: existing ICCS are still expensive and only available in limited models of car. As a result of that, only a small number of drivers can obtain a car equipped with an ICCS, especially in developing countries. The second problem is that existing ICCS are not aware of the driving context, which plays a role in distracting drivers. This research project was based on the following thesis statement: A mobile, context-aware model can be designed to reduce driver distraction caused by the use of ICCS. A mobile ICCS is portable and can be used in any car, addressing the first problem. Context-awareness will be used to detect possible situations that contribute to distracting drivers and the interaction with the mobile ICCS will be adapted so as to avert calls and text messages. This will address the second problem. As the driving context is dynamic, drivers may have to deal with critical safety-related tasks while they are using an existing ICCS. The following steps were taken in order to validate the thesis statement. An investigation was conducted into the causes and consequences of driver distraction. A review of literature was conducted on context-aware techniques that could potentially be used. The design of a model was proposed, called the Multimodal Interface for Mobile Info-communication with Context (MIMIC) and a preliminary usability evaluation was conducted in order to assess the feasibility of a speech-based, mobile ICCS. Despite some problems with the speech recognition, the results were satisfying and showed that the proposed model for mobile ICCS was feasible. Experiments were conducted in order to collect data to perform supervised learning to determine the driving context. The aim was to select the most effective machine learning techniques to determine the driving context. Decision tree and instance-based algorithms were found to be the best performing algorithms. Variables such as speed, acceleration and linear acceleration were found to be the most important variables according to an analysis of the decision tree. The initial MIMIC model was updated to include several adaptation effects and the resulting model was implemented as a prototype mobile application, called MIMIC-Prototype.

The purpose of this thesis is to make a survey of the growth and development of safety. Safety-consciousness in the individual may be developed by determining the educational contributions that have been made in the field of safety by industrial and social organizations.

Indiana University-Purdue University Indianapolis (IUPUI) / One of the biggest hurdles to the development of an effective driver state monitor is the that there is no real-time eye-gaze detection. This is primarily due to the fact that such systems require calibration. In this thesis the various aspects that comprise an eye gaze tracker are investigated. From that we developed an eye gaze tracker for automobiles that does not require calibration. We used a monocular camera system with IR light sources placed in each of the three mirrors. The camera system created the bright-pupil effect for robust pupil detection and tracking. We developed an SVM based algorithm for initial eye candidate detection; after that the eyes were tracked using a hybrid Kalman/Mean-shift algorithm. From the tracked pupils, various features such as the location of the glints (reflections in the pupil from the IR light sources) were extracted. This information is then fed into a Generalized Regression Neural Network (GRNN). The GRNN then maps this information into one of thirteen gaze regions in the vehicle.

Indiana University-Purdue University Indianapolis (IUPUI) / Traffic accidents cause millions of injuries and tens of thousands of fatalities per year worldwide. This thesis briefly reviews different types of active safety systems designed to reduce the number of accidents. Focusing on lane departure, a leading cause of crashes involving fatalities, we examine a lane-keeping system proposed by Minoiu Enache et al.They proposed a switched linear feedback (LMI) controller and provided two switching laws, which limit driver torque and displacement of the front wheels from the center of the lane. In this thesis, a state feedback (LQR) controller has been designed. Also, a new switching logic has been proposed which is based on driver's torque, lateral offset of the vehicle from the center of the lane and relative yaw angle. The controller activates assistance torque when the driver is deemed inattentive. It is deactivated when the driver regains control. Matlab/Simulink modeling and simulation environment is used to verify the results of the controller. In comparison to the earlier switching strategies, the maximum values of the state variables lie very close to the set of bounds for normal driving zone. Also, analysis of the controller’s root locus shows an improvement in the damping factor, implying better system response.

Road traffic safety has been a subject of worldwide concern. Dedicated short range communications (DSRC) is widely regarded as a promising enabling technology for collaborative safety applications (CSA), which can provide robust communication and affordable performance to build large scale CSA system. The main focus of this thesis is to develop solutions for DSRC QoS control in order to provide robust QoS support for CSA. The first design objective is to ensure robust and reliable message delivery services for safety applications from the DSRC networks. As the spectrum resources allocated to DSRC network are expected to be shared by both safety and non-safety applications, the second design objective is to make QoS control schemes bandwidth-efficient in order to leave as much as possible bandwidth for non-safety applications. The first part of the thesis investigates QoS control in infrastructure based DSRC networks, where roadside access points (AP) are available to control QoS control at road intersections. After analyse DSRC network capabilities on QoS provisioning without congestion control, we propose a two-phases adaptive QoS control method for DSRC vehicle networks. In the first phase an offline simulation based approach is used to and out the best possible system configurations (e.g. message rate and transmit power) with given numbers of vehicles and QoS requirements. It is noted that with different utility functions the values of optimal parameters proposed by the two phases centralized QoS control scheme will be different. The conclusions obtained with the proposed scheme are dependent on the chosen utility functions. But the proposed two phases centralized QoS control scheme is general and is applicable to different utility functions. In the second phase, these configurations are used online by roadside AP adaptively according to dynamic traffic loads. The second part of the thesis is focused on distributed QoS control for DSRC networks. A framework of collaborative QoS control is proposed, following which we utilize the local channel busy time as the indicator of network congestion and adaptively adjust safety message rate by a modified additive increase and multiplicative decrease (AIMD) method in a distributed way. Numerical results demonstrate the effectiveness of the proposed QoS control schemes.

Traumatic brain injury (TBI) is a major problem with an estimated cost of $76 billion per year in the US alone. The Center for Disease Control and Prevention (CDC) documented 2.53 million TBI-related emergency department visits, with approximately 288,000 TBI-related hospitalizations and 56,800 TBI-related deaths in 2014 in the US. The lack of FDA-approved treatment strategies for TBI drives the need for novel therapeutic and preventative measures. In a quest to reduce TBI-related injuries and deaths, automotive companies have focused their efforts to make safer cars for both occupants and pedestrians. Computational finite element (FE) models have been used to advance research efforts in automotive safety systems engineering in hopes of ameliorating the burden caused by TBI. The current use of FE models in the automotive industry focuses on predicting stresses and strains that occur during the accident itself to predict primary injury. However, contemporary models lack the appropriate mechanical properties required to make accurate predictions of brain tissue deformation after injury and lack the ability to model secondary injuries such as cerebral edema (brain swelling). With cerebral edema being a major cause of death and disability after TBI, and with the pattern and magnitude of cerebral edema being dependent on the initiating strain field in brain tissue during TBI, automotive safety systems could be further improved if 1) FE head models contained more accurate mechanical properties and 2) if FE models could simulate secondary injuries such as cerebral edema. Therefore, the driving purpose of this thesis is two-fold: 1) to determine the mechanical properties of different regions of the brain and 2) to present a new computational methodology that allows for modeling of cerebral edema to better predict patient outcome following TBI. The use of FE models requires appropriate constitutive formulations and associated parameters to accurately model and predict the initial mechanical response of the brain to injury loading conditions. Since patient outcome is dependent on the resulting strain field within brain tissue post-injury, accurate modeling of brain tissue deformation is important for testing the efficacy of engineered automotive safety systems using FE simulations. To address this need, the first aim of this thesis employed an inverse FE approach to characterize mechanical properties of the human hippocampus (CA1, CA3, dentate gyrus), cortex white matter, and cortex gray matter. Anatomical regions were significantly different in their mechanical properties. Although no sex dependency was observed, there were trends indicating that some male brain regions were generally stiffer than corresponding female regions. In addition, mechanical properties were not dependent on age within the examined age range (4-58 years old). Ultimately, this study provides a structure-specific description of fresh human brain tissue mechanical properties, which will be an important step toward explicitly modeling the heterogeneity of brain tissue deformation during TBI using FE modeling. Fatal brain injuries may also result from physiological changes in the brain that occur after the primary injury that immediately occurs during head injury. Secondary injuries such as cerebral edema are associated with poor outcome. Despite the severe consequences of cerebral edema, its mechanism is not fully understood. The second aim of this thesis, therefore, was to elucidate the driving mechanism of cerebral edema by demonstrating that cleavage of intracellular fixed-charge density (FCD) reduces brain swelling pressure and to measure the FCD content of rat and pig brain tissue. Thin brain samples were placed into a confined pressure chamber, and FCD content was calculated from measured swelling pressure and the Gibbs-Donnan equation. We observed that cleavage of FCD using enzymes reduced swelling pressure in rat brain tissue samples and determined that pig cortex gray matter contains more FCD than pig cortex white matter. These results demonstrate that cerebral edema may occur in accordance with principles of triphasic swelling biomechanics and demonstrates the plausibility of computationally modeling cerebral edema with triphasic material formulations. Cerebral edema leads to increased intracranial pressure (ICP) as the brain swells within the fixed volume of the skull, and there is overwhelming evidence of ICP as a powerful predictor of patient outcome following TBI. Current industry standards of patient outcome evaluation use tissue-level metrics solely from primary injury such as maximum principal strain (MPS) or cumulative strain damage measure (CSDM), but these methods can be improved especially in regards to predicting mortality. Therefore, the third aim of this thesis was to develop a new FE head model and computational methodology incorporating triphasic swelling biomechanics to simulate brain swelling following impact to improve patient outcome predictions. Patient outcome was predicted by simulating swelling and calculating the resulting ICP, which is a strong indicator of patient mortality. Calculating ICP in addition to predicting primary injury metrics such as MPS and CSDM may allow automotive safety engineers to make better predictions of patient outcome following TBI so they can develop better safety systems. Another common indicator of poor outcome following TBI is acute subdural hematoma (ASDH). ASDH is an intracranial bleed that often results from TBI because of stretching and tearing of the bridging veins which causes blood to collect in the innermost layer of the dura. Despite the poor prognosis associated with the presence of ASDH following TBI, the mechanism as to why its presence is associated with a higher likelihood of death remains uncertain. Current state of the art FE head models used in automotive safety engineering efforts do not consider ASDH, which may drastically reduce their effectiveness in predicting patient outcome following TBI. Therefore, the fourth and final aim of this thesis was to incorporate ASDH into our FE head model of swelling and elucidate the underlying secondary brain injury mechanism of ASDH that contributes to increased mortality in hopes of increasing the efficacy of current FE models to predict patient outcome and ultimately design better safety systems. Using our novel FE head model and methodology from aim 3, we showed that the higher likelihood of death associated with the presence of ASDH may be caused by exacerbated ischemic injury which increases ICP, demonstrating that modeling of ASDH is necessary for accurately modeling patient outcome following TBI. Despite decades of TBI research and FE head model improvements, more work is required to enhance the biofidelity of these models to better predict patient outcome. The work in this thesis is important, as it introduces a new tool that will allow automotive safety engineers to incorporate cerebral edema and ASDH, both of which may drastically influence patient outcome following TBI, into models of head injury to allow for better predictions of patient outcome. It is hoped that the work in this thesis lays the foundation for future work that aids in the design of improved automotive safety systems that will save countless human lives.

Indiana University-Purdue University Indianapolis (IUPUI) / The Pedestrian Automatic Emergency Braking System (PAEB) can utilize on-board sensors to detect pedestrians and take safety related actions. However, PAEB system only benefits the individual vehicle and the pedestrians detected by its PAEB. Additionally, due to the range limitations of PAEB sensors and speed limitations of sensory data processing, PAEB system often cannot detect or do not have sufficient time to respond to a potential crash with pedestrians. For further improving pedestrian safety, we proposed the idea for integrating the complimentary capabilities of V2V and PAEB (V2V-PAEB), which allows the vehicles to share the information of pedestrians detected by PAEB system in the V2V network. So a V2V-PAEB enabled vehicle uses not only its on-board sensors of the PAEB system, but also the received V2V messages from other vehicles to detect potential collisions with pedestrians and make better safety related decisions. In this thesis, we discussed the architecture and the information processing stages of the V2V-PAEB system. In addition, a comprehensive Matlab/Simulink based simulation model of the V2V-PAEB system is also developed in PreScan simulation environment. The simulation result shows that this simulation model works properly and the V2V-PAEB system can improve pedestrian safety significantly.