Lateral control of autonomous vehicle by yaw rate feedback

Hong, Seong Jae; Choi, Jae Yeon; Jeong, Yoong Ki; Jeong, Kum Young; Lee, Man Hyung; Park, None Kyeong Taik; Yoon, Kang Sup; Hur, Nam Su

doi:10.1007/bf03185231

Cited by 13 publications

(12 citation statements)

References 11 publications

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“…To improve the accuracy of a vehicle model in simulation, bushing is considered between suspension systems and chassis [3]. A bushing made of rubber is modeled as each threedimensional translational spring damper actuator (TSDA) and rotational spring damper actuator (RSDA).…”

Section: Multi Body Dynamic Vehicle Modelmentioning

confidence: 99%

“…Yaw rate and lateral acceleration as lateral performance are calculated by the classical single-track model which is obtained by lumping the two front wheels as one wheel in the centerline of the vehicle (the same is done with the two rear wheels) [3]. For the lateral direction and the yaw axis, the vehicle kinetics at the CG are described as…”

Section: Two Degrees Of Freedom Vehicle Modelmentioning

confidence: 99%

“…Lateral control, or lane-keeping, involves autonomously guiding the vehicle to reference trajectories. By using the relative lateral offset and heading of the vehicle, various lateral control algorithms have previously been proposed [1][2][3], and Ref. [4].…”

Section: Introductionmentioning

confidence: 99%

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Robust controller for an autonomous vehicle with look-ahead and look-down information

Choi

2011

J Mech Sci Technol

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For the lateral control of an autonomous vehicle, this paper proposes a linear-matrix-inequality (LMI)-based H ∞ control algorithm that utilizes the feedback of the lateral offset and target yaw angle at the preview point, which is effective for the fusion of look-ahead and look-down sensors. To verify the performance of this controller, lane change and circular lane tracking simulations are carried out in multi body dynamics. Against the uniformly random noises in position and yaw angle and the constant modeling uncertainties in mass and cornering stiffness, the robustness of the proposed algorithm is compared with the cubic curve method and the heading angle method at the look-ahead target lane.

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Section: Multi Body Dynamic Vehicle Modelmentioning

confidence: 99%

Section: Two Degrees Of Freedom Vehicle Modelmentioning

confidence: 99%

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Robust controller for an autonomous vehicle with look-ahead and look-down information

Choi

2011

J Mech Sci Technol

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“…The inputs to the vehicle model are steering angle, brake pressure, vehicle speed, wind velocity, and the condition of the road. In the HILS system needed in the development of the EPS system, the steering angle and vehicle speed is received to output the tire lateral force (Choi et al, 2002;Salaani et al, 2002).…”

Section: Seventeen-degree-freedom Vehicle Model For Hilsmentioning

confidence: 99%

Development of a hardware in the loop simulation system for electric power steering in vehicles

Lee

et al. 2011

Int.J Automot. Technol.

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In this paper, a hardware-in-the-loop simulation (HILS) system was developed before the development of an electric power steering (EPS) system in a vehicle. This study was focused on the establishment of the HILS system. Driving conditions are simulated with the HILS system. The actual steering input parameters are confirmed on the monitor while driving the HILS system. The steering forces observed in the simulation with the developed HILS system are similar to those in real vehicle tests. The developed HILS system can be applied in the development of various types of EPS systems.

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“…Essas máquinas são meios de produção altamente especializados, tornando a supervisão do processo produtivo como a principal tarefa dos operadores. Guiar tais veículos, apesar de não ser a principal função do operador exige grande parte de sua atenção influenciando diretamente na produtividade dá area cultivada (CHOI et al , 2002).…”

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Método de extração da posição de máquinas agrícolas por visão computacional baseado em redes pulsadas e ponto de fuga

Neris¹

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A minha querida esposa, Vânia, e ao meu eterno mestre Silvio. AgradecimentosAo meu orientador, Prof. Dr. Valentin Obac Roda, pela orientação, pelo apoio e por todo o conhecimento que me foi transmitido.A Vânia, minha esposa, pelo carinho e por sua compreensão e apoio durante a elaboração deste trabalho.Aos meus pais, irmãos e avós pelo incentivo, apoio e carinho.A empresa AGX Tecnologia Ltda. por autorizar a utilização do sistema AGpilot e aos colegas de trabalho pelo incentivo.A Universidade de São Paulo pela estrutura e suporte.A todos os companheiros do laboratório pelas discussões técnicas e amizade.A todos os professores e funcionários do Departamento de Engenharia Elétrica da EESC/ USP e a todos aqueles que, de uma forma ou de outra, contribuíram para a realização deste trabalho. A redução de custos e a melhora do processo produtivo são essenciais para o aumento da rentabilidade e da produtividade dasáreas agrícolas. O investimento em tecnologia se torna, portanto, fundamental em um mundo cada vez mais competitivo. Neste trabalhó e apresentado o desenvolvimento de um método de extração da posição de máquinas agrícolas, em relaçãoàs linhas de cultivo, a partir do processamento de imagens fornecidas por uma câmera de vídeo colorida. A posição extraídaé a informação básica utilizada em um sistema de direcionamento automático, permitindo determinar quais ações devam ser tomadas para manter a máquina em sua trajetória. O correto posicionamento da máquina sobre as linhas de cultivo melhora o processo de pulverização, ocasionando a redução de custos e o aumento da produtividade daárea. O método proposto está embasado nos conceitos de ponto de fuga e busca antecipada. Essas técnicas permitiram simplificar o processamento das imagens e conseqüentemente a redução do tempo de processamento.Essas características, aliadas ao correto posicionamento da câmera, devem permitir que o método proposto possa ser utilizado no controle de máquinas agrícolas que operam em grandes velocidades como os pulverizadores.Palavras-chave: controle automático; GPS; visão computacional; redes neurais pulsadas; ponto de fuga Cost reduction and productive process improvement are essential to increase yield in agricultural areas. Investments in technology become, therefore, important in a competitive world. This work presents a novel approach for extracting agricultural machine position, with respect to crop rows, processing images captured by a color video camera. The correct machine positioning in crop rows can improve agricultural processes such as spraying, decreasing the costs and increasing the area yield. The proposed method is based on the look-ahead and vanishing points techniques. These techniques allow the reduction of the algorithm complexity and, therefore, the reduction of the processing time. These characteristics added to the camera position may allow the system to control agricultural machines that run at high speeds, such as sprayers. Motivação e RelevânciaO setor agrícola brasileiro tem se destacado cada vez mais pelos rec...

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Lateral control of autonomous vehicle by yaw rate feedback

Cited by 13 publications

References 11 publications

Robust controller for an autonomous vehicle with look-ahead and look-down information

Robust controller for an autonomous vehicle with look-ahead and look-down information

Development of a hardware in the loop simulation system for electric power steering in vehicles

Método de extração da posição de máquinas agrícolas por visão computacional baseado em redes pulsadas e ponto de fuga

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