The goal of this work was to compensate for the effects of the Earth’s magnetic field in a vector field magnetic sensor. The magnetic sensor is a part of a low-cost crash avoidance system by Stephane Roussel where the magnetic sensor was used to detect cars passing when it was mounted to a test vehicle. However, the magnetic sensor’s output voltage varied when it changed orientation with respect to the Earth’s magnetic field. This limited the previous work to only analyze detection rates when the test vehicle travelled a single heading. Since one of the goals of this system is to be low-cost, the proposed solution for geomagnetic compensation will only use a single magnetic sensor and a consumer-grade GPS. Other solutions exist for geomagnetic compensation but use extra sensors and can become costly. In order to progress the development of this project into a commercial project, three separate geomagnetic compensation algorithms and a calibration procedure were developed. The calibration procedure compensated for the local magnetic field when the magnetic sensor was mounted to the test vehicle and allowed for consistent magnetic sensor voltage output regardless of the type of test vehicle. The first algorithm, Compensation Scheme 1 (CS1), characterized the local geomagnetic field with a mathematical function from field calibration data. The GPS heading was used as the input and the output is the voltage level of the Earth’s magnetic field. The second algorithm, Compensation Scheme 1.5, used a mathematical model of the Earth’s magnetic field using the International Geomagnetic Reference Field. An algorithm was developed to take GPS coordinates as an input and output the voltage contributed by the mathematical representation of the Earth’s magnetic field. The output voltages from CS1 and CS1.5 were subtracted from the calibrated magnetic sensor data. The third algorithm, Compensation Scheme 2 (CS2), used a high pass filter to compensate for changes of orientation of the magnetic sensor. All three algorithms were successful in compensating for the geomagnetic field and vehicle detection in multiple car headings was possible. Since the goal of the magnetic sensor is to detect vehicles, vehicle detection rates were used to evaluate the effectiveness of the algorithms. The individual algorithms had limitations when used to detect passing cars. Through testing, it was found that CS1 and CS1.5 algorithms were suitable to detect vehicles while stopped in traffic while the CS2 algorithm was suitable vehicle detection while the test vehicle is moving. In order to compensate for the limitations of the individual algorithms, a fused algorithm was developed that used a combination of CS1 and CS2 or CS1.5 and CS2. The vehicle speed was used in order to determine which algorithm to use in order to detect cars. Although the goal of this project is not vehicle detection, the rate of successful vehicle detection was used in order to evaluate the algorithms. The evaluation of the fused algorithm demonstrated the value of using CS1 and CS1.5 to detect vehicles when stopped in traffic, which CS2 algorithm cannot do. For a study conducted in traffic, using the fused algorithm increased vehicle detection rates by 51%-62% from using the CS2 algorithm alone. Since this work successfully compensated for geomagnetic effects of the magnetic sensor, the low-cost crash avoidance system can be further developed since it is no longer limited to driving in a single direction. Other projects that experience unwanted geomagnetic effects in their projects can also implement the knowledge and solutions used in this work.

Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system. / DIPLECS / GARNICS / CUAS

The aim of electrification of chassis and driveline systems in road vehicles is to reduce the global emissions and their impact on the environment. The electrification of such systems in vehicles is enabling a whole new set of functionalities improving safety, handling and comfort for the user. This trend is leading to an increased number of elements in road vehicles such as additional sensors, actuators and software codes. As a result, the complexity of vehicle components and subsystems is rising and has to be handled during operation. Hence, the probability of potential faults that can lead to component or subsystem failures deteriorating the dynamic behaviour of road vehicles is becoming higher. Mechanical, electric, electronic or software faults can cause these failures independently or by mutually influencing each other, thereby leading to potentially critical traffic situations or even accidents. There is a need to analyse faults regarding their influence on the dynamic behaviour of road vehicles and to investigate their effect on the driver-vehicle interaction and to find new control strategies for fault handling. A structured method for the classification of faults regarding their influence on the longitudinal, lateral and yaw motion of a road vehicle is proposed. To evaluate this method, a broad failure mode and effect analysis was performed to identify and model relevant faults that have an effect on the vehicle dynamic behaviour. This fault classification method identifies the level of controllability, i.e. how easy or difficult it is for the driver and the vehicle control system to correct the disturbance on the vehicle behaviour caused by the fault. Fault-tolerant control strategies are suggested which can handle faults with a critical controllability level in order to maintain the directional stability of the vehicle. Based on the principle of control allocation, three fault-tolerant control strategies are proposed and have been evaluated in an electric vehicle with typical faults. It is shown that the control allocation strategies give a less critical trajectory deviation compared to an uncontrolled vehicle and a regular electronic stability control algorithm. An experimental validation confirmed the potential of this type of fault handling using one of the proposed control allocation strategies. Driver-vehicle interaction has been experimentally analysed during various failure conditions with typical faults of an electric driveline both at urban and motorway speeds. The driver reactions to the failure conditions were analysed and the extent to which the drivers could handle a fault were investigated. The drivers as such proved to be capable controllers by compensating for the occurring failures in time when they were prepared for the eventuality of a failure. Based on the experimental data, a failure-sensitive driver model has been developed and evaluated for different failure conditions. The suggested fault classification method was further verified with the conducted experimental studies. The interaction between drivers and a fault-tolerant control system with the occurrence of a fault that affects the vehicle dynamic stability was investigated further. The control allocation strategy has a positive influence on maintaining the intended path and the vehicle stability, and supports the driver by reducing the necessary corrective steering effort. This fault-tolerant control strategy has shown promising results and its potential for improving traffic safety. / <p>QC 20150520</p>

This thesis analyzes the human as an element of accident system in the sphere of motor-vehicle traffic. Then interprets the risks, damages and injuries in this sphere which are caused by the driver. On this basis, the measures to reduce the number of injuries in the Czech Republic are drawn up. In this thesis is taken account of existing measures that were proceeded in this area. It focuses particularly on the subject "driver" and its role in traffic accidents.

O aumento no número de veículos tem levado a um exagerado aumento das colisões. Para diminuir a quantidade e a gravidade dos acidentes, a segurança veicular passou a ser um ponto determinante na concepção de um automóvel. Dentre as principais frentes de estudo da segurança veicular está a redução da energia cinética transmitida aos ocupantes quando de uma colisão. Neste caso, os projetos de veículos empregam absorvedores de impacto, também conhecidos pelo termo em inglês crash box, para absorver a energia cinética do impacto em energia de deformação da estrutura. Este estudo tem por objetivo avaliar o desempenho dos absorvedores de energia mais comuns na literatura e na indústria. A avaliação ocorre por meio de simulações numéricas usando o método dos elementos finitos e por considerações teóricas de várias medidas de eficiência. Uma vez identificados os absorvedores de melhor desempenho ao impacto, estes são considerados como base para análises paramétricas de forma e material de modo a se aumentar sua eficiência. / The increase in vehicle production has lead to an increase in the number os colisions. To reduce the amount and severity of accident vehicle safety became an important issue in automobile design. Among the main vehicle safety researches is the reduction in the kinectic energy transmitted to the occupants in a colision event. Impact absorbers or crash boxes transform the impact kinectic energy into plastic deformation. This research aims to asses the performance of the most common energy absorbers used in the industry. The assesment is done trough numerical simulations by finite element analysis and trough theoretical approaches using different effciency measures. The most successful absorbers are used as basis for optimizing its shape and material usage.

No description available.

Li-ion batteries (LIB) are used in many applications because of their high-power/energy density, long life cycling, and low self-discharge rate. The use of LIB continues to grow every day, and the necessity for proper safety standards grows as well. A key aspect for safe utilization of LIB is determining their safety and remaining useful life (RUL). Battery characteristics degrade over time under normal and extreme operating conditions and modeling the electrochemical processes can improve RUL estimations. Extreme operating conditions such as abnormal temperatures and charge/discharge rates are believed to exacerbate the rate of degradation. Li-ion batteries are also susceptible to mechanical damage, which may lead to an electrical short. In severe cases, mechanical damage causes a thermal run away, and possibly explosions or fires. In the event of a car accident, battery packs can be damage without an electrical short or immediate thermal run away. Currently, there is no reliable batt / Mechanical Engineering

Autonomous Vehicles (AVs) should result in tremendous benefits to safe human transportation. Recent reports indicate a global average of 3,287 road crash related fatalities a day with the blame, in most cases, assigned to the human driver. By replacing the main cause, AVs are predicted to significantly reduce road accidents -- some claiming up to a 90% reduction on US roads. However, achieving these numbers is not simple. AVs are expected to assume tasks that human drivers perform both consciously and unconsciously -- in some instances, with Machine Learning. AVs incur new levels of complexity that, if handled incorrectly, can result in failures that cause loss of human life and damage to the environment. Accidents involving SAE Level 2 vehicles have highlighted such failures and demonstrated that AVs have a long way to go. The path towards safe AVs includes system architectures that provide effective failure monitoring, detection and mitigation. These architectures must produce AVs that degrade gracefully and remain sufficiently operational in the presence of failures. We introduce Safe-AV, a fault tolerant safety architecture for AVs that is based on the commonly adopted E-Gas 3 Level Monitoring Concept, the Simplex Architecture and guided by a thorough hazard analysis in the form of Systems-Theoretic Process Analysis (STPA). We commenced the architecture design with a review of some modern AV accidents which helped identify the types of failures AVs can present and acted as a first step to our STPA. The hazard analysis was applied to an initial AV architecture (without safety mechanisms) consisting of components that should be present in a typical AV (based on the literature and our ideas). Our STPA identified the system level accidents, hazards and corresponding loss scenarios that led to well-founded safety requirements which, in turn, evolved the initial architecture into Safe-AV. / Thesis / Master of Applied Science (MASc)

Great loads occur on human body in traffic accidents. Children body have less resistance to these loads. Child Restraint Systems (CRS) are the safety elements used in vehicles for children. In this study, the overturning and the dynamic test setups for CRS, have been designed and analysed according to United Nations Economic Commission for Europe Regulation No 44 (ECE R44). After manufacturing of the test setups, four different types of CRSs sold in Turkish market have been selected to evaluate their performance according to ECE R44. Each seat has been used once for the tests. The tests have been performed and evaluated according to the performances of CRSs for the dynamic test head displacement limit criterion, the acceleration limit criterion, the abdominal penetration criterion and the overturning head displacement limit criterion. 11 overturning tests and 8 dynamic tests at the sled test facility available in METU-BILTIR Center Vehicle Safety Unit have been conducted. In the tests, P-series 3 years, 6 years and 10 years old child test dummies have been used. During the dynamic tests, 3-axial accelerometer, high-g high speed camera and data acquisition system are also used to gather the test data. 8 more dynamic test with unlocked vehicle safety belt which is improper usage and commonly encountered in real life. As the result of the tests, none of the CRSs succeed in the tests for child seats which are supposed to be used by 3-6 years old children according to ECE R 44 Group II.

Active vehicle safety systems for road vehicles play an important role in accident prevention. In recent years, rapid developments have been observed in this area with advancing technology and electronic control systems. Active yaw control is one of these subjects, which aims to control the vehicle in case of any impending spinning or plowing during rapid and/or sharp maneuver. In addition to the development of these systems, integration and cooperation of these independent control mechanisms constitutes the current trend in active vehicle safety systems design. In this thesis, design methodology and simulation results of an active yaw control system for two axle road vehicles have been presented. Main objective of the yaw control system is to estimate the desired yaw behavior of the vehicle according to the demand of the driver and track this desired behavior accurately. The design procedure follows a progressive method, which first aims to design the yaw control scheme without regarding any other stability parameters, followed by the development of the designed control scheme via taking other stability parameters such vehicle sideslip angle into consideration. A two degree of freedom vehicle model (commonly known as &ldquo / Bicycle Model&rdquo / ) is employed to model the desired vehicle behavior. The design of the controller is based on Fuzzy Logic Control, which has proved itself useful for complex nonlinear design problems. Afterwards, the proposed yaw controller has been modified in order to limit the vehicle sideslip angle as well. Integration of the designed active yaw control system with other safety systems such as Anti-Lock Braking System (ABS) and Traction Control System (TCS) is another subject of this study. A fuzzy logic based wheel slip controller has also been included in the study in order to integrate two different independent active systems to each other, which, in fact, is a general design approach for real life applications. This integration actually aims to initiate and develop the integration procedure of the active yaw control system with the (ABS). An eight degree of freedom detailed vehicle model with nonlinear tire model is utilized to represent the real vehicle in order to ensure the validity of the results. The simulation is held in MATLAB/Simulink environment, which has provided versatile design and simulation capabilities for this study. Wide-ranging simulations include various maneuvers with different road conditions have been performed in order to demonstrate the performance of the proposed controller.