Existe necessidade de se desenvolver modelos teóricos e testes experimentais, que nos permitam ter plenas condições de melhor avaliar e concluir sobre o comportamento dinâmico dos ônibus, ao trafegar sobre diferentes pistas e realizar diversos tipos de manobras. O objetivo do trabalho é avaliar e otimizar simultaneamente o comportamento dinâmico lateral e vertical de um ônibus modelado como um sistema multicorpo. A metodologia utilizada no trabalho é dividida em duas partes. A primeira parte consiste na programação de um modelo multicorpo de ônibus que possa ser utilizado para fins de otimização do seu comportamento de dinâmica lateral via programação matemática; o desenvolvimento de uma manobra do tipo mudança dupla de faixa - DLC (Double Lane Change), adaptada da combinação da norma ISO 3888-1:1999 que envolve mudança dupla de faixa para carros de passeio e a norma ISO 14791:2000 que envolve mudança simples de faixa para veículos comerciais, na ausência de normas específicas; e finalmente a validação de resultados através de testes experimentais e simulações computacionais. A segunda parte consiste na programação de um modelo multicorpo de ônibus para fins de otimização do seu comportamento de dinâmica vertical via programação matemática, neste caso sujeito a uma pista da classe C segundo classificação da norma ISO 8608:1995. Os resultados específicos da programação das manobras laterais do modelo de ónibus foram validados experimentalmente, bem como comparados através da simulação das manobras num modelo virtual implementado num software multicorpo comercial. O conjunto das soluções atingidas mostraram boa correlação, possibilitando a posterior otimização dos parâmetros concentrados da suspensão do modelo multicorpo de ônibus, através da técnica de algoritmos genéticos. A função objetivo implementada consiste da composição penalizada do valor RMS do ângulo de rolagem da manobra lateral quanto ao handling, e de parâmetros associados ao conforto e segurança, como o valor RMS da aceleração vertical, do deslocamento máximo da suspensão, e da deflexão máxima do pneu de forma a garantir aderência continua à pista. Os resultados otimizados dos parâmetros concentrados conseguem uma negociação dos objetivos conflitantes. / There is a need for theoretical models and experimental tests to be developed that allow for better assessments and conclusions about the dynamic behavior of buses driving on different lanes and performing various types of maneuvers. The purpose of this work is to evaluate and optimize both the lateral and the vertical dynamic behavior of a bus modeled as a multibody system. The methodology employed comprises two parts. The first part consists in programming a bus multibody model that can be used to optimize the lateral dynamic behavior of buses via mathematical programming; developing a type of maneuver known as Double Lane Change (DLC), adapted from a combination of the ISO 3888-1:1999 standard, which involves double lane changes for passenger cars, and the ISO 14791:2000 standard, which involves single lane changes for commercial vehicles, in the absence of specific standards; and lastly, validating the results by means of experimental tests and computational simulations. The second part consists in programming a bus multibody model to optimize the vertical dynamic behavior via mathematical programming, in this case for a class C road, according to the classification of the ISO 8608:1995 standard. The specific results of the programming of the lateral maneuvers of the bus model were validated experimentally and then compared with simulations of the maneuvers by a virtual model developed using commercial multibody software. The results showed a good correlation, enabling subsequent optimization of the lumped parameters of the suspension of the bus multibody model using the genetic algorithm optimization technique. The objective function consists of the penalized composition of some terms, including the RMS value of the roll angle of the lateral handling maneuver and of parameters associated with comfort and safety, such as the RMS value of vertical acceleration, the maximum suspension working space, and the maximum tire deflection to ensure continuous adherence on the road surface. The optimized results of the lumped parameters of the suspension enable an alignment of the conflicting goals.

abstract: Driving a vehicle is a complex task that typically requires several physical interactions and mental tasks. Inattentive driving takes a driver’s attention away from the primary task of driving, which can endanger the safety of driver, passenger(s), as well as pedestrians. According to several traffic safety administration organizations, distracted and inattentive driving are the primary causes of vehicle crashes or near crashes. In this research, a novel approach to detect and mitigate various levels of driving distractions is proposed. This novel approach consists of two main phases: i.) Proposing a system to detect various levels of driver distractions (low, medium, and high) using a machine learning techniques. ii.) Mitigating the effects of driver distractions through the integration of the distracted driving detection algorithm and the existing vehicle safety systems. In phase- 1, vehicle data were collected from an advanced driving simulator and a visual based sensor (webcam) for face monitoring. In addition, data were processed using a machine learning algorithm and a head pose analysis package in MATLAB. Then the model was trained and validated to detect different human operator distraction levels. In phase 2, the detected level of distraction, time to collision (TTC), lane position (LP), and steering entropy (SE) were used as an input to feed the vehicle safety controller that provides an appropriate action to maintain and/or mitigate vehicle safety status. The integrated detection algorithm and vehicle safety controller were then prototyped using MATLAB/SIMULINK for validation. A complete vehicle power train model including the driver’s interaction was replicated, and the outcome from the detection algorithm was fed into the vehicle safety controller. The results show that the vehicle safety system controller reacted and mitigated the vehicle safety status-in closed loop real-time fashion. The simulation results show that the proposed approach is efficient, accurate, and adaptable to dynamic changes resulting from the driver, as well as the vehicle system. This novel approach was applied in order to mitigate the impact of visual and cognitive distractions on the driver performance. / Dissertation/Thesis / Doctoral Dissertation Applied Psychology 2017

Existe necessidade de se desenvolver modelos teóricos e testes experimentais, que nos permitam ter plenas condições de melhor avaliar e concluir sobre o comportamento dinâmico dos ônibus, ao trafegar sobre diferentes pistas e realizar diversos tipos de manobras. O objetivo do trabalho é avaliar e otimizar simultaneamente o comportamento dinâmico lateral e vertical de um ônibus modelado como um sistema multicorpo. A metodologia utilizada no trabalho é dividida em duas partes. A primeira parte consiste na programação de um modelo multicorpo de ônibus que possa ser utilizado para fins de otimização do seu comportamento de dinâmica lateral via programação matemática; o desenvolvimento de uma manobra do tipo mudança dupla de faixa - DLC (Double Lane Change), adaptada da combinação da norma ISO 3888-1:1999 que envolve mudança dupla de faixa para carros de passeio e a norma ISO 14791:2000 que envolve mudança simples de faixa para veículos comerciais, na ausência de normas específicas; e finalmente a validação de resultados através de testes experimentais e simulações computacionais. A segunda parte consiste na programação de um modelo multicorpo de ônibus para fins de otimização do seu comportamento de dinâmica vertical via programação matemática, neste caso sujeito a uma pista da classe C segundo classificação da norma ISO 8608:1995. Os resultados específicos da programação das manobras laterais do modelo de ónibus foram validados experimentalmente, bem como comparados através da simulação das manobras num modelo virtual implementado num software multicorpo comercial. O conjunto das soluções atingidas mostraram boa correlação, possibilitando a posterior otimização dos parâmetros concentrados da suspensão do modelo multicorpo de ônibus, através da técnica de algoritmos genéticos. A função objetivo implementada consiste da composição penalizada do valor RMS do ângulo de rolagem da manobra lateral quanto ao handling, e de parâmetros associados ao conforto e segurança, como o valor RMS da aceleração vertical, do deslocamento máximo da suspensão, e da deflexão máxima do pneu de forma a garantir aderência continua à pista. Os resultados otimizados dos parâmetros concentrados conseguem uma negociação dos objetivos conflitantes. / There is a need for theoretical models and experimental tests to be developed that allow for better assessments and conclusions about the dynamic behavior of buses driving on different lanes and performing various types of maneuvers. The purpose of this work is to evaluate and optimize both the lateral and the vertical dynamic behavior of a bus modeled as a multibody system. The methodology employed comprises two parts. The first part consists in programming a bus multibody model that can be used to optimize the lateral dynamic behavior of buses via mathematical programming; developing a type of maneuver known as Double Lane Change (DLC), adapted from a combination of the ISO 3888-1:1999 standard, which involves double lane changes for passenger cars, and the ISO 14791:2000 standard, which involves single lane changes for commercial vehicles, in the absence of specific standards; and lastly, validating the results by means of experimental tests and computational simulations. The second part consists in programming a bus multibody model to optimize the vertical dynamic behavior via mathematical programming, in this case for a class C road, according to the classification of the ISO 8608:1995 standard. The specific results of the programming of the lateral maneuvers of the bus model were validated experimentally and then compared with simulations of the maneuvers by a virtual model developed using commercial multibody software. The results showed a good correlation, enabling subsequent optimization of the lumped parameters of the suspension of the bus multibody model using the genetic algorithm optimization technique. The objective function consists of the penalized composition of some terms, including the RMS value of the roll angle of the lateral handling maneuver and of parameters associated with comfort and safety, such as the RMS value of vertical acceleration, the maximum suspension working space, and the maximum tire deflection to ensure continuous adherence on the road surface. The optimized results of the lumped parameters of the suspension enable an alignment of the conflicting goals.

Diploma thesis will be addressed about issue of vehicle inspection at Inspection stations in Czech republic and neighboring countries. Thesis will be concentrate about legislation, metodics, evaluation of technical condition and influence of dangerous faults to vehicle operation. One part of thesis will be proposal of provision to increase safety in vehicle tradic.

<p>Unsafe lane changes have been identified as a common factor in motor vehicle accidents. It would be helpful, particularly for automated vehicles, to know if there are behaviors of vehicles, beyond a directional signal, or characteristics of the traffic environment that correlated with a higher probability of an unsafe lane change (lane changes without a directional signal). This work investigates what the observable cues are that drivers use to determine the relative safety when overtaking front vehicles, and if drivers make more lane changes under certain conditions on highways. This study utilizes interviews, surveys, 3D animation software, and highway driving public footage for data collection and experiments. It is found that a side-to-side motion of the front vehicle or a factor that might trigger a side-to-side motion of the front vehicle in the environment is the key marker that indicates a possible unsafe lane change, and it is also found that traffic speed, time of day, traffic flow, and a combination of traffic density & number of lanes & vehicle count all have effects on drive’s decision on making lane changes on different levels.</p>

No description available.

The "Actively Caring for KIDS Process," a multi-component program that taught retail store sales associates to act as behavior-change agents for child passenger safety, was implemented at a nationwide-chain discount store and evaluated with an interrupted time series design and a similar control site for comparison. Key components of the KIDS Process included a) training of sales associates to act as behavior-change agents at the point-of-purchase, b) the use of in-store awareness and supportive materials such as posters and sales associate buttons, and c) incentives for participation in checkpoints. Safety-seat checks (n = 31) were held in store parking lots, where caregivers' safety-seat installations (n = 241) were recorded as safe or at-risk for a variety of criteria and then the seats were reinstalled correctly. Research assistants posing as child caregivers visited the retail stores (n = 156) with the purported objective of obtaining information about selecting and installing a safety seat. Information given by sales associates was systematically recorded as safe or at-risk on a checklist. A 2 (Store) x 2 (Phase) ANOVA on sales associates' percent safe information scores revealed a significant interaction and no main effects. The Control store did not differ across the two phases, but scores at the intervention store were significantly higher after the intervention than during pre-intervention and when compared to the Control store during post-intervention. The training of sales associates resulted in an average 65% increase in percent safe scores. At the parking lot checks, 93 percent of seats checked were misused in one or more ways, with an average of four errors per seat. ANOVA and Chi-square analyses indicated that the intervention failed to have an impact on child safety-seat misuse observed or on the number of participants attending the checkpoints. This is likely a result of few parents attending the checkpoints who had talked to our trained associates. To target more parents, this intervention might be better placed at well-baby checkups. / Ph. D.

The dynamic behavior of a vehicle is predominantly controlled by the forces and moments generated at the contact patch between the tire and the road surface. As a result, tire characteristics can dramatically change vehicle response, especially during maneuvers that yields the tires to reach to the limits of its adhesion capacity. To assist the driver in such cases and to prevent other possible instability scenarios, various vehicle control systems e.g. anti-lock brakes (ABS), stability controllers (ESP, ESC) or rollover mitigation schemes are introduced, which are generally known as active vehicle safety systems. Based on the above facts, one can easily come to the conclusion that to improve upon the current control algorithms developed for the technology in use; a vehicle control system design requires accurate knowledge of the tire states. This study proposes the use of a smart tire system that can provide information on momentary variation of tire features through the sensor units attached directly on the tire and develops control algorithms based on this information to assure the match-up between tire and controller dynamics. A prototype smart tire system was developed for field testing and for detailed analysis of its potential. Based on the collected prototype data, novel observer and controller schemes were developed to obtain dynamic tire state information and to improve vehicle handling performance. The proposed algorithms were implemented and evaluated using numerical analysis in Matlab/SimulinkR environment. For a more realistic simulation environment, vehicle models were integrated from Mechanical Simulations CarSimR® software suite. / Ph. D.

The development of Automated Driving Systems (ADS) has been ongoing for decades in varying levels of sophistication. Levels of automation are defined by Society of American Engineers (SAE) as 0 through 5, with 0 being full human control and 5 being full automation control. Another way to describe levels of automation is through concepts of Functional Safety (FuSa) and Operational Safety (OpSa). These terms of FuSa and OpSa are important, because ADS testing relies on both. Current recommendations for ADS testing include both OpSa and FuSa requirements. However, an examination of ADS safety requirements (e.g., industry reports, post-crash analysis reports, etc.) reveals that ADS safety arguments, in practice, depend almost completely on well-trained human operators, referred to in the industry as in vehicle fallback test drivers (IFTD). To date, the industry has never fielded a truly SAE L4 ADS on public roads due to this persistent hurdle of needing a human operator for Operational Safety. There is a tendency in ADS testing to reference International Standards Organization (ISOs) for validated vehicles for vehicles that are still in development (i.e., unvalidated). To be clear, ISOs for ADS end products are not necessarily applicable to ADS in development. With this in mind, there is a clear gap in the industry for unvalidated ADS literature. Because of this gap, ADS testing for unvalidated vehicles often relies on safety requirements for validated vehicles. This issue remains a significant challenge for ADS testing. Recognizing this gap in on-road, in-development vehicle safety, there is a need for the ADS industry to develop a clear strategy for transitioning from an IFTD (Operational Safety) to an ADS (Functional Safety). Therefore, the purpose of this thesis is to present a framework for transitioning from Operational Safety to Functional Safety. The framework makes this possible through an inductive analysis of available definitions of onroad safety to arrive at a definition that leverages Functional and Operational Safety along a continuum. Ultimately, the framework aims to contribute to onroad safety testing for the ADS industry. / Master of Science / The development of Self-Driving Cars has been ongoing for decades in varying levels of sophistication. Levels of automation are defined by Society of American Engineers (SAE) as 0 through 5, with 0 being full human control and 5 being full automation control. Another way to describe levels of automation is through concepts of Robotic Control and Human Control. If a vehicle relies completely on Human Control, a human operator is responsible for all on-road safety. On the other hand, a fully autonomous would be considered fully in Robotic Control. These terms of Robotic Control and Human Control are important, because Self-Driving Car testing relies on both. Current recommendations for Self-Driving Car testing include both Robotic Control and Human Control requirements. However, an examination of Self-Driving Cars documentation (e.g., industry reports, post-crash analysis reports, etc.) reveals that Self-Driving Car safety arguments, in practice, depend almost completely on well-trained human operators. To date, the industry has never fielded a truly SAE L4 Self-Driving Car on public roads due to this persistent hurdle of needing a human operator for Human Control. There is a tendency in Self-Driving Car testing to reference standars for validated vehicles for vehicles that are still in development (i.e., unvalidated). To be clear, standards for Self-Driving Car end products are not necessarily applicable to Self-Driving Cars in development. With this in mind, there is a clear gap in the industry for unvalidated Self-Driving Car literature. Because of this gap, Self-Driving Car testing for unvalidated vehicles often relies on documentation for validated vehicles. This issue remains a significant challenge for Self-Driving Car testing. Recognizing this gap in on-road, in-development vehicle safety, there is a need for the Self-Driving industry to develop a clear strategy for transitioning from Human Control to Robot Control. Therefore, the purpose of this thesis is to present a framework for transitioning from Human to Robot Control. The framework makes this possible through an inductive analysis of available definitions of onroad safety to arrive at a definition that leverages all definitions of Safety along a continuum. Ultimately, the framework aims to contribute to onroad safety testing for the Self-Driving industry.

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.