Relevant bibliographies by topics / Autonomous steering

Academic literature on the topic 'Autonomous steering'

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Published: 14 March 2023

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Journal articles on the topic "Autonomous steering"

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Mohamad, Amir Ashraf, Fadhlan Hafizhelmi Kamaru Zaman, and Fazlina Ahmat Ruslan. "Improving steering convergence in autonomous vehicle steering control." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 1 (January 1, 2019): 279. http://dx.doi.org/10.11591/ijeecs.v13.i1.pp279-285.

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<p>Steering control is a critical design element in autonomous vehicle development since it will determine whether the vehicle can navigate safely or not. For the prototype of UiTM Autonomous Vehicle 0 (UiTM AV0), Vexta motor is used to control the steering whereas Pulse Width Modulation (PWM) signal is responsible to drive the motor. However, by using PWM signal it is difficult to converge to the desired steering angle and furthermore time taken for steering angle to converge is much longer. Thus, Proportional Integral Derivative (PID) has been introduced in this autonomous vehicle steering controller to improve the convergence of the steering. Meanwhile a microcontroller was used to control the Vexta Motor direction and perform the calculation of the desired steering angle. Simulation results showed PID controller showed better time taken and preicison of successful convergence of the desired steering angle compared to the PWM controller. Analysis results showed that PID controller significantly reduce the overshooting of steering angle and significantly improve the time taken for convergence by up to 37 seconds faster than PWM controller in UiTM AV0.</p>
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Pushpakanth, Abhishek, and Mangesh N. Dhavalikar. "Development of Steering Control System for Autonomous Vehicle." International Journal of Recent Technology and Engineering (IJRTE) 11, no. 2 (July 30, 2022): 50–53. http://dx.doi.org/10.35940/ijrte.b7105.0711222.

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Automation can help us to reduce the number of crashes on our roads. Through research it is identified that 94 percent of the accidents that occur are because of driver behavior or error as a factor and self-driving vehicles can help reduce driver error. High levels of automation have the potential to reduce risky and dangerous driver behavior and prevent accidents. The main aim is to convert the manual operated steering of the vehicle into fully autonomous steering. The objective of Steering Control System is to control the vehicle’s steering while the vehicle is in motion and also to take accurate decisions while making a turn from the given inputs. The main purpose to develop a steering system for the autonomous vehicle is to replace the manual steering of the vehicle into driverless steering. The steering control is responsible for the vehicle’s steering i.e., at what desired angle the vehicle need to turn. A PID (Proportional Integral Derivative) controller and an encoder is basically used to control the system based on the necessary conditions and requirement’s. For the vehicle’s steering the encoder is used to generate pulses when the steering wheel is turned so that those pulse values can be sent to the DC Motor which is attached to the front axle which is responsible for the vehicle to turn. This autonomous vehicle is a Level-4 automation system and the benefit of this automation is that the vehicle can be even operated in manual mode whenever it’s necessary.
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Shi, Haozhe, Guoqing Geng, Xing Xu, Ju Xie, and Shenguang He. "Path Tracking Control of Intelligent Vehicles Considering Multi-Nonlinear Characteristics for Dual-Motor Autonomous Steering System." Actuators 12, no. 3 (February 23, 2023): 97. http://dx.doi.org/10.3390/act12030097.

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In the path tracking control of intelligent vehicles, the traditional linear control method is prone to high tracking errors for uncertain parameters of the steering transmission system and road conditions. Therefore, considering the mechanical friction in the dual-motor autonomous steering system and the nonlinearity of tires, this paper proposes a path tracking control strategy of intelligent vehicles for the dual-motor autonomous steering system that considers nonlinear characteristics. First, a dual-motor autonomous steering system considering mechanical friction and the variation of tire cornering stiffness under different tire–road friction coefficients was established based on the structure of an autonomous steering system. Second, a tire–road friction coefficient estimator was designed based on a PSO-LSTM neural network. The tire cornering stiffness under different tire–road friction coefficients was estimated through the recursive least-square algorithm. Then, the control strategy of the dual-motor autonomous steering system was designed by combining the LQR path tracking controller with the adaptive sliding mode control strategy based on field-oriented control. Here, mechanical friction and the variation of tire cornering stiffness were considered. Finally, simulation and HiL tests validated the method proposed in this paper. The results show that the proposed control strategy significantly improves the tracking accuracy and performance of the dual-motor autonomous steering system for intelligent vehicles.
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INOUE, Keiichi. "STEERING CONTROL SYSTEM FOR AUTONOMOUS TRACTOR." Proceedings of the JFPS International Symposium on Fluid Power 2008, no. 7-1 (2008): 53–58. http://dx.doi.org/10.5739/isfp.2008.53.

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Eidehall, Andreas, Jochen Pohl, Fredrik Gustafsson, and Jonas Ekmark. "Toward Autonomous Collision Avoidance by Steering." IEEE Transactions on Intelligent Transportation Systems 8, no. 1 (March 2007): 84–94. http://dx.doi.org/10.1109/tits.2006.888606.

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TSUGAWA, Sadayuki, and Satoshi MURATA. "Steering Control Algorithm for Autonomous Vehicle." Transactions of the Institute of Systems, Control and Information Engineers 2, no. 10 (1989): 360–62. http://dx.doi.org/10.5687/iscie.2.360.

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Liu, Runqiao, Minxiang Wei, and Nan Sang. "Emergency obstacle avoidance trajectory tracking control based on active disturbance rejection for autonomous vehicles." International Journal of Advanced Robotic Systems 17, no. 3 (May 1, 2020): 172988142092110. http://dx.doi.org/10.1177/1729881420921105.

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To solve the problem of understeer and oversteer for autonomous vehicle under high-speed emergency obstacle avoidance conditions, considering the effect of steering angular frequency and vehicle speed on yaw rate for four-wheel steering vehicles in the frequency domain, a feed-forward controller for four-wheel steering autonomous vehicles that tracks the desired yaw rate is proposed. Furthermore, the steering sensitivity coefficient of the vehicle is compensated linearly with the change in the steering angular frequency and vehicle speed. In addition, to minimize the tracking errors caused by vehicle nonlinearity and external disturbances, an active disturbance rejection control feedback controller that tracks the desired lateral displacement and desired yaw angle is designed. Finally, CarSim® obstacle avoidance simulation results show that an autonomous vehicle with the four-wheel steering path tracking controller consisting of feed-forward control and feedback control could not only improve the tire lateral forces but also reduce tail flicking (oversteer) and pushing ahead (understeer) under high-speed emergency obstacle avoidance conditions.
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Arifin, Bustanul, Bhakti Yudho Suprapto, Sri Arttini Dwi Prasetyowati, and Zainuddin Nawawi. "Steering Control in Electric Power Steering Autonomous Vehicle Using Type-2 Fuzzy Logic Control and PI Control." World Electric Vehicle Journal 13, no. 3 (March 17, 2022): 53. http://dx.doi.org/10.3390/wevj13030053.

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The steering system in autonomous vehicles is an essential issue that must be addressed. Appropriate control will result in a smooth and risk-free steering system. Compared to other types of controls, type-2 fuzzy logic control has the advantage of dealing with uncertain inputs, which are common in autonomous vehicles. This paper proposes a novel method for the steering control of autonomous vehicles based on type-2 fuzzy logic control combined with PI control. The primary control, type-2 fuzzy logic control, has three inputs—distance, navigation, and speed. The fuzzy system’s output is the steering angle value. This was used as input for the secondary control, PI control. This control is in charge of adjusting the motor’s position as a manifestation of the steering angle. The study results applied to the EPS system of autonomous vehicles revealed that type-2 fuzzy logic control and PI control produced better and smoother control than type-1 fuzzy logic control and PI. The slightest disturbance in the type-1 fuzzy logic control showed a significant change in steering, while this did not occur in the type-2 fuzzy logic control. The results indicate that type-2 fuzzy logic control and PI control could be used for autonomous vehicles by maintaining the comfort and safety of the users.
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Li, Guo Qiang, and Xing Ye Wang. "Research on Electronic Pneumatic Steering and Braking Control Technology for Autonomous Tracked Vehicles." Applied Mechanics and Materials 577 (July 2014): 359–63. http://dx.doi.org/10.4028/www.scientific.net/amm.577.359.

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To realize the autonomous driving of a certain tracked vehicle, the paper has a research on its steering and braking control technology. According to the steering and braking device’s structure and work principle on the original vehicle, the paper design an electronic pneumatic steering and braking control system before analyzing the design request of the system and introduce the system’s work principle. Applying this system to the original vehicle’s autonomous transformation, a test was conducted on the vehicle, the test prove that the electronic pneumatic steering and braking control system can well satisfied the tracked vehicles’ request of steering and braking.
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Leng, Bo, Yehan Jiang, Yize Yu, Lu Xiong, and Zhuoping Yu. "Distributed drive electric autonomous vehicle steering angle control based on active disturbance rejection control." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 235, no. 1 (August 6, 2020): 128–42. http://dx.doi.org/10.1177/0954407020944288.

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Based on active disturbance rejection control technique and characteristics of electric power steering, a steering angle tracking controller is designed, which consists of an aligning moment estimator to deal with modeling error and nonlinearity of electric power steering. The aligning moment estimator is based on an extended state observer and takes steering system friction and differential drive steering torque, which is a unique phenomenon in a distributed drive electric vehicle, into consideration. According to the estimated aligning moment and tracking differentiator, the steering angle tracking controller is designed based on a nonlinear state feedback control and feedforward compensation control laws. Results of various simulations and experiments, including pivot steering, step input steering, and sinusoidal input steering, show that the proposed controller has good performance in tracking reference steering angle and is convenient to implement. With the aligning moment estimator, the proposed controller shows better results in comparative experiments than a conditional integral-based steering angle tracking controller.
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Dissertations / Theses on the topic "Autonomous steering"

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Magnusson, Filip. "Evaluating Deep Learning Algorithms for Steering an Autonomous Vehicle." Thesis, Linköpings universitet, Programvara och system, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153450.

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With self-driving cars on the horizon, vehicle autonomy and its problems is a hot topic. In this study we are using convolutional neural networks to make a robot car avoid obstacles. The robot car has a monocular camera, and our approach is to use the images taken by the camera as input, and then output a steering command. Using this method the car is to avoid any object in front of it. In order to lower the amount of training data we use models that are pretrained on ImageNet, a large image database containing millions of images. The model are then trained on our own dataset, which contains of images taken directly by the robot car while driving around. The images are then labeled with the steering command used while taking the image. While training we experiment with using different amounts of frozen layers. A frozen layer is a layer that has been pretrained on ImageNet, but are not trained on our dataset. The Xception, MobileNet and VGG16 architectures are tested and compared to each other. We find that a lower amount of frozen layer produces better results, and our best model, which used the Xception architecture, achieved 81.19% accuracy on our test set. During a qualitative test the car avoid collisions 78.57% of the time.
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Brown, William Shaler. "Technology for Designing the Steering Subsystem Component of an Autonomous Vehicle." Thesis, Virginia Tech, 2007. http://hdl.handle.net/10919/34960.

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Autonomous vehicles offer means to complete unsafe military operations without endangering the lives of soldiers. Such solutions have fueled many efforts towards designing autonomous, or unmanned, systems. Military and academic research efforts alike continue to focus on developing these systems. While many different autonomous vehicles have been introduced, however, such complex systems have limited drive-by-wire operability. The complete process to up-fit a vehicle to fully autonomous operation involves the design, up-fit, testing and verification of many different subsystems. The objective of this thesis is to design and model an autonomous steering system requiring little modifications to an existing steering system. It is desirable to still operate the vehicle manually as well as preserve the vehicleâ s visual appearance. Up-fit and implementation of the designed steering system and verification of its functionality has been documented as well. Utilization of the supplied controller and software has enabled the testing and characterization of the system. The proposed design offers a solution to a wide variety of wheeled vehicles steered via the traditional and common steering wheel method. In addition, modifications have been made to an existing simulation of an unmanned vehicle in a military testbed environment (Fort Benning). The simulation accounts for the control methodology as it has been designed and tested with, which offers the ability to analyze the dynamics of the unmanned system.
Master of Science
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Meidenbauer, Kennneth Richard. "An Investigation of the Clothoid Steering Model for Autonomous Vehicles." Thesis, Virginia Tech, 2007. http://hdl.handle.net/10919/34279.

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The clothoid, also known as the Cornu spiral, is a curve generated by linearly increasing or decreasing curvature as a function of arc length. The clothoid has been widely accepted as a logical curve for transitioning from straight segments to circle arcs in roads and railways, because a vehicle following the curve at constant speed will have a constant change of centripetal acceleration. Clothoids have also been widely adopted in planning potential paths for autonomous vehicle navigation. They have been viewed as useful representations of possible trajectories that are dynamically feasible. Surprisingly, the assumptions that underlie this choice appear to be lightly treated or ignored in past literature. This thesis will examine three key assumptions that are implicitly made when assuming that a vehicle will follow a clothoid path. The first assumption is that the vehicle's steering mechanism will produce a linear change in turning radius for a constant rate input. This assumption is loosely referred to as the "bicycle model" and it relates directly to the kinematic parameters of the steering mechanism. The second assumption is that the steering actuator can provide a constant steering velocity. In other words, the actuator controlling the steering motion can instantaneously change from one rate to another. The third assumption is that the vehicle is traveling at a constant velocity. By definition, the clothoid is a perfect representation of a vehicle traveling at constant velocity with a constant rate of change in steering curvature. The goal of this research was to examine the accuracy of these assumptions for a typical Ackermann-steered ground vehicle. Both theoretical and experimental results are presented. The vehicle that was used as an example in this study was a modified Club Car Pioneer XRT 1500. This Ackermann-steered vehicle was modified for autonomous navigation and was one of Virginia Tech's entries in the DARPA 2005 Grand Challenge. As in typical operation, path planning was conducted using the classic clothoid curve model. The vehicle was then commanded to drive a selected path, but with variations in speed and steering rate that are inherent to the real system. The validity of the three assumptions discussed above were examined by comparing the actual vehicle response to the planned clothoid. This study determined that the actual paths driven by the vehicle were generally a close match to the originally planned theoretical clothoid path. In this study, the actual kinematics of the Ackermann vehicle steering system had only a small effect on the driven path. This indicates that the bicycle model is a reasonable simplification, at least for the case studied. The assumption of constant velocity actuation of the steering system also proved to be reasonably accurate. The greatest deviation from the planned clothoid path resulted from the nonlinear velocity of the vehicle along the path, especially when accelerating from a stop. Nevertheless, the clothoid path plan generally seems to be a good representation of actual vehicle motion, especially when the planned path is updated frequently.
Master of Science
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Haglund, Sebastian, and Henrik Johansson. "Steering Control During μ-split Braking for an Autonomous Heavy Road Vehicle." Thesis, Linköpings universitet, Fordonssystem, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166962.

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A critical maneuver for a heavy vehicle is braking with different friction on the left and right hand side of the vehicle, called μ-split. This results in an unwanted yaw torque acting on the vehicle. During this situation, the driver maintains the lateral stability and follows the desired path by corrective steering. In anautonomous heavy vehicle the system must handle this situation by itself. The purpose of this thesis is to analyze how an autonomous vehicle can detect a μ-split situation and then use steering control to maintain its path and stability. Two methods for detecting a μ-split situation are presented where one is based on vehicle kinematics, this detector utilizes the difference in wheel speed between the left and right hand side of the vehicle. The other detector is based on lateral vehicle dynamics, this method uses a sliding mode observer to detect unexpected changes in the yaw rate signal. The detectors were tested in a real vehicle and the results showed that the kinematic detector was fast but had a small risk of false detection, while the dynamic detector was slower but more robust. An analysis of the desired steering behavior showed that the steady state during μ-split braking is to drive with a non zero body slip. If a kinematic path follower is used with kinematic error dynamics this will lead to a contradicting behavior since the body slip is equal to the heading error during straight line braking, assuming that the velocity vector of the vehicle is parallel to the path. Simulations showed that during a μ-split situation the Linear Quadratic pathfollower based on kinematic error dynamics manages to follow the path with a non zero body slip while keeping the path errors small. It has also been shown how the detection of a μ-split situation can be used to change control strategy. By introducing active yaw control or change the tuning on the controller after a detection a better result could be achieved.
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Lerider, Malcolm. "Autonomous Calibration and Control of Mine Vehicles." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-91034.

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The mining industry desires to cut costs and to operate in more dangerous mines, which is why companies such as Atlas Copco are developing autonomous vehicles. The problem to navigate autonomously is however complex, so the vehicles have in the recent years become more intelligent; the number of computers, actuators and sensors are increasing. For example, an autonomous LHD (Loading – Hauling – Dump) vehicle has sensors including: inertial measurement unit (IMU), odometer, hinge angle sensor, laser range finders and cameras. The parameters for the sensors needs to be calibrated before the vehicle can be used in a mine. There are also a number of electrical currents which needs to be calibrated for the actuators.The calibration of parameters has traditionally been made manually, but Atlas Copco realizes that manual calibration is not feasible once the sales of intelligent mine vehicles increases. Effort is therefore put into automation of the calibration procedures.Interviews with employees were carried out at Atlas Copco to identify the most time consuming procedures during calibration and installation of autonomous mine vehicles. The calibration of steering currents was not only identified as the most time consuming procedure, but also as one of the most complex procedures.The goal of this thesis is to enable easier and quicker installation of mine vehicles. This is done through investigation of methods for automatic calibration of steering currents. The problem is approached from two angles: a grey box model using system identification and a black box model using neural network with resilient backpropagation. The models are compared to a search algorithm, used for simulation of the manual calibration method. In the end, the models are evaluated with regard to performance and ease of implementation.The hypothesis was that the more complex grey box or black box model would have higher accuracy than a simple search algorithm. However, the search algorithm proves to outperform the other models both with regard to accuracy and calibration time, and is also easier to implement. The search algorithm is thus suggested to be implemented instead of a complex model. Moreover, it is suggested that a straightforward mapping of 20 currents may outperform even the search calibration. It is also concluded that calibration of steering currents can be done when the vehicle is standing still.
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Hawkinson, Todd D. "Multiple input sliding mode control for autonomous diving and steering of underwater vehicles." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA241935.

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Thesis (M.S. in Mechanical Engineering and Mechanical Engineer)--Naval Postgraduate School, December 1990.
Thesis Advisor(s): Papoulias, Fotis A. "December 1990." Description based on title screen as viewed on March 31, 2010. DTIC Identifier(s): Autonomous, Guidance Control, Theses. Author(s) subject terms: Autonomous Underwater Vehicles, AUV, Guidance Control. Includes bibliographical references (p. 195). Also available in print.
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Campbell, Stefan F. (Stefan Forrest). "Steering control of an autonomous ground vehicle with application to the DARPA Urban Challenge." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42301.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.
Includes bibliographical references (p. 156-157).
Fundamental to the design of an Ackerman steered autonomous ground vehicle is the development of a low-level controller that effectively performs trajectory or path tracking. Though ample literature is available on various methods for controlling ground vehicles, little information is presented on the implementation and tuning of such controllers. Moreover, few sources extend ground vehicle control to driving in reverse. This work presents a novel approach to the implementation of the traditional "pure pursuit" style controller in which a dynamic vehicle model is used to map from the path curvature specified by the pure pursuit algorithm to the vehicle's actual steering angle. Additionally, an analytical methodology using a linear model of straight-line path following is used to tune the pure pursuit look-ahead distance. This pure pursuit controller is then contrasted with a simulation-based controller that uses a kinematic model to predict the vehicle's response to a series of different steering inputs; a performance metric is used to select the best command given these predictions. Successful trajectory control results are presented at speeds up to 22 mph. The second focus of this work is the control of a front-wheel steered vehicle driving in reverse. Novel to this work is the presentation of pure pursuit as a stable solution to this problem. Pure pursuit is then contrasted with the mechanism-based controller that was developed by Patwardhan et al. at the University of California Berkeley. In presenting this controller, a new method employing a linear kinematic vehicle model is used to tune the controller parameters. It is then shown that, under specific conditions, the mechanism-based controller and the pure pursuit controller are identical. Both controllers are then compared with the simulation-based controller adapted for driving in reverse.
(cont.) Results are presented at speeds up to 6.7 mph. Results for the implementation of these controllers were collected using a 2006 Land Rover LR3 developed for MIT's entry into the 2007 DARPA Urban Challenge. Results ultimately illustrate the respective strengths and weaknesses of the pure pursuit class of controllers.
by Stefan F. Campbell.
S.M.
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Wetterlind, Victor. "Concept development of steering column : Accommodating business commuters in a level four autonomous car." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-68135.

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This thesis reports on a collaborative concept development with Volvo Car Corporation. The problem underlying the concept development was to innovate a steering device for a level-four autonomous car. Specifically: How can the steering wheel and its mount be designed to give the driver more room when the car can drive itself? The product development process was combined with a hybrid strategy view, both an in-side-out and outside-in approach. The thesis is written by the project leader Victor Wetterlind for his bachelor’s thesis in Innovation and design engineering at Karlstad University. This with supervision from postdoctoral researcher within innovation, Jakob Trischler and examiner, professor in manufacturing engineering, Leo de Vin. The thesis corresponds to 22.5 hp and belongs to the faculty of health, science and technology. Along the project, analysis of field tests, research on related subjects, discussions with experts and lead-users were held. Concepts were created with both individual and group-based methods. The project has used computer-aided design as a tool to test concepts along the evaluation phase. 2-D and 3-D models were used to perceived size, proportion and design as well as for digitally verifying kinematics and function. After several evaluation iterations and concept refinement, a concept recommendation was done to the company in the shape of a presentation and 3D-model.
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GUIDOLINI, R. "A NEURAL-BASED MODEL PREDICTIVE CONTROL TO TACKLE STEERING DELAY OF THE IARA AUTONOMOUS CAR." Universidade Federal do Espírito Santo, 2017. http://repositorio.ufes.br/handle/10/9852.

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Made available in DSpace on 2018-08-02T00:03:50Z (GMT). No. of bitstreams: 1 tese_11489_Dissertacao_Mestrado_Ranik_Guidolini.pdf: 1818285 bytes, checksum: aa13e12658434d1e3f0f9ffb83d197fb (MD5) Previous issue date: 2017-09-04
Neste trabalho, propomos uma abordagem de Controle Preditivo Baseado em Modelo Neural (Neural Based Model Predictive Control - N-MPC) para lidar com atrasos na planta de direção de carros autônomos. Examinamos a abordagem N-MPC como uma alternativa para a implementação do subsistema de controle de direção da Intelligent and Autonomous Robotic Automobile (IARA). Para isso, comparamos a solução padrão, baseada na abordagem de controle Proporcional Integral Derivativo (PID), com a abordagem N-MPC. O subsistema de controle de direção PID funciona bem na IARA para velocidades de até 25 km/h. No entanto, acima desta velocidade, atrasos na Planta de Direção da IARA são muito elevados para permitir uma operação adequada usando uma abordagem PID. Modelamos a Planta de Direção da IARA usando uma rede neural e empregamos esse modelo neural na abordagem N-MPC. A abordagem N-MPC superou a abordagem PID reduzindo o impacto de atrasos na Planta de Direção de IARA e permitindo a operação autônoma da IARA em velocidades de até 37 km/h um aumento de 48% na velocidade máxima estável
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Striedieck, Robert. "LOOPHOLE : How sports cars will find a way to survive the autonomous future." Thesis, Umeå universitet, Designhögskolan vid Umeå universitet, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136854.

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What will happen to sport cars once our society and infrastructure allow for a fully autonomous transport systems? My concern for the ”survival of the sports car” clearly originates from an emotional viewpoint rather than a reasonable argument. We know about the benefits that come along with autonomy but that doesn’t make the fear of loosing the emotional side of driving unfounded. My aim was to create a scenario that allows both reason and emotion to coexist and furthermore to benefit from each other rather than to create a conflict. The result is a PORSCHE for 2040 that shows an exciting concept for steering fully autonomous cars of the future. It combines the benefits of autonomy with the emotions of sports cars.
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Books on the topic "Autonomous steering"

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McGhee, Robert B. A simulation study of an autonomous steering system for on-road operation of automotive vehicles. Monterey, California: Naval Postgraduate School, 1986.

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Tan, Chiam Huat. A simulation study of an autonomous steering system for on-road operation of automotive vehicles. 1986.

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Rhodes, R. A. W. The New Governance. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198786108.003.0010.

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The chapter reviews the several definitions of governance: the minimal state; corporate governance; the new public management, ‘good’ governance; a socio-cybernetic system. It then stipulates a definition of governance as self-organizing, inter-organizational networks. It argues there is a trend from government to governance in British government because of the hollowing-out pressures and the tools for intergovernmental management are integral to effective steering. Policy networks are already widespread. This trend is not widely recognized and has important implications not only for the practice of British government but also for democratic accountability. Governance as self-organizing networks is a challenge to governability because the networks can become autonomous and resist central guidance. They are set fair to become the prime example of governing without government.
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Book chapters on the topic "Autonomous steering"

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Naranjo, J. E., C. González, R. García, and T. de Pedro. "Electric Power Steering Automation for Autonomous Driving." In Lecture Notes in Computer Science, 519–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11556985_67.

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Gim, Suhyeon, Lounis Adouane, Sukhan Lee, and Jean-Pierre Derutin. "Parametric Continuous Curvature Path for Smooth Steering with Car-like Vehicles." In Intelligent Autonomous Systems 13, 1327–42. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08338-4_96.

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Lee, Hyosang, and Jung Kim. "Estimation of Needle Deflection in Layered Soft Tissue for Robotic Needle Steering." In Intelligent Autonomous Systems 13, 1133–44. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08338-4_82.

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Caenazzo, Alberto, and Kaspar Althoefer. "Hypertonic Saline Solution for Signal Transmission and Steering in MRI-Guided Intravascular Catheterisation." In Towards Autonomous Robotic Systems, 284–90. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96728-8_24.

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Choi, Wansik, Hyun-Sik Nam, Byungjoo Kim, and Changsun Ahn. "Model Predictive Control for Evasive Steering of Autonomous Vehicle." In Lecture Notes in Mechanical Engineering, 1252–58. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38077-9_144.

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Yamaguchi, Hiroaki, Ryosuke Takahashi, and Atsushi Kawakami. "Control of a Four-Forked Steering Walker—Design of Virtual Mechanical Elements Based on Desired Motions." In Intelligent Autonomous Systems 13, 1271–84. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08338-4_92.

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Wu, Zhe, Yidu Zhang, Qiong Wu, and Jiangfan Wu. "Analysis of Autonomous Vehicle Steering System and Route Planning Method." In Advances in Intelligent Systems and Computing, 787–93. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8944-2_91.

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Kuhnert, Klaus-Dieter, and Michael Krödel. "Autonomous Vehicle Steering Based on Evaluative Feedback by Reinforcement Learning." In Machine Learning and Data Mining in Pattern Recognition, 405–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11510888_40.

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Sarif, Nira Mawangi, Rafidah Ngadengon, Herdawatie Abdul Kadir, and Mohd Hafiz A. Jalil. "Discrete Sliding Mode Controller on Autonomous Underwater Vehicle in Steering Motion." In Lecture Notes in Electrical Engineering, 163–76. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5281-6_12.

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Max, György, Sándor Vass, and Bálint Kiss. "Development of Robust H-Infinity Steering Control System for Autonomous Vehicles." In Lecture Notes in Mechanical Engineering, 393–402. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75677-6_34.

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Conference papers on the topic "Autonomous steering"

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Jazar, Reza N., M. Mahinfalah, and A. Khazaei. "Four-Wheel Steering Autonomous Vehicles." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-11407.

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Employing an independent four-wheel-steering (4WS) system, we introduce an autodriver algorithm to keep an autonomous vehicle on a given road. The kinematic condition of steering can be used to set the steer angles such that the kinematic center of rotation is at a desired point. The road and tire characteristics, along with the dynamics of a moving vehicle cause the vehicle to turn about an actual point that is not necessarily at the road curvature center. The position of the dynamic turning center can be controlled by adjusting the steer angles such that it coincides with the road curvature center. Such a vehicle will move on the desired road autonomously.
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Mori, Kinji. "Steering Chair's message." In 2009 International Symposium on Autonomous Decentralized Systems (ISADS). IEEE, 2009. http://dx.doi.org/10.1109/isads.2009.5207398.

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"Steering Committee." In 2021 Fourth International Conference on Connected and Autonomous Driving (MetroCAD). IEEE, 2021. http://dx.doi.org/10.1109/metrocad51599.2021.00008.

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Galvane, Quentin, Marc Christie, Rémi Ronfard, Chen-Kim Lim, and Marie-Paule Cani. "Steering Behaviors for Autonomous Cameras." In Motion. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2522628.2522899.

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Bajcinca, Naim. "Autonomous all-wheel car steering." In 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control. IEEE, 2006. http://dx.doi.org/10.1109/cacsd-cca-isic.2006.4776827.

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Bajcinca, Naim. "Autonomous all-wheel car steering." In 2006 IEEE International Conference on Control Applications. IEEE, 2006. http://dx.doi.org/10.1109/cca.2006.286023.

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Cortner, Alex, James M. Conrad, and Nabila A. BouSaba. "Autonomous all-terrain vehicle steering." In SOUTHEASTCON 2012. IEEE, 2012. http://dx.doi.org/10.1109/secon.2012.6196932.

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Dev, Vishnu S., V. V. Sajith Variyar, and K. P. Soman. "Steering angle estimation for autonomous vehicle." In 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2017. http://dx.doi.org/10.1109/icacci.2017.8125951.

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Zhao, Kangqiao, Feng Lin, and Hock S. Seah. "Steering autonomous animals in VR hunting." In International Workshop on Advanced Image Technology 2021, edited by Wen-Nung Lie, Qian Kemao, Jae-Gon Kim, and Masayuki Nakajima. SPIE, 2021. http://dx.doi.org/10.1117/12.2587233.

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Jazar, Reza N., Milan Simic, and A. Khazaei. "Autodriver Algorithm for Autonomous Vehicle." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-37609.

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In a recent research a superior algorithm has been introduced to design an autodriver to keep an autonomous vehicle on a given road using independent four-wheel-steering (4WS) system. The kinematic condition of steering sets the steer angles such that the kinematic center of rotation of the vehicle be controlled on a two dimensional space. The vehicle however, will turn about an actual point that is not necessarily at the road curvature center; because of the road, tire characteristics, and dynamics of the moving vehicle. The algorithm shows how the position of the dynamic turning center can be controlled by adjusting the steer angles such that it coincides with the road curvature center. Such a vehicle will move on the desired road autonomously. In this paper, the required facilities to apply the algorithm experimentally will be discussed.
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Reports on the topic "Autonomous steering"

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Quinn, Brian, Jordan Bates, Michael Parker, and Sally Shoop. A detailed approach to autonomous vehicle control through Ros and Pixhawk controllers. Engineer Research and Development Center (U.S.), November 2021. http://dx.doi.org/10.21079/11681/42460.

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A Polaris MRZR military utility vehicle was used as a testing platform to develop a novel, low cost yet feature-rich, approach to adding remote operation and autonomous driving capability to a military vehicle. The main concept of operation adapts steering and throttle output from a low cost commercially available Pixhawk autopilot controller and translates the signal into the necessary inputs for the Robot Operating System (ROS) based drive by wire system integrated into the MRZR. With minimal modification these enhancements could be applied to any vehicle with similar ROS integration. This paper details the methods and testing approach used to develop this autonomous driving capability.
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Gregow, Hilppa, Antti Mäkelä, Heikki Tuomenvirta, Sirkku Juhola, Janina Käyhkö, Adriaan Perrels, Eeva Kuntsi-Reunanen, et al. Ilmastonmuutokseen sopeutumisen ohjauskeinot, kustannukset ja alueelliset ulottuvuudet. Suomen ilmastopaneeli, 2021. http://dx.doi.org/10.31885/9789527457047.

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The new EU strategy on adaptation to climate change highlights the urgency of adaptation measures while bringing forth adaptation as vitally important as a response to climate change as mitigation. In order to provide information on how adaptation to climate change has been promoted in Finland and what calls for attention next, we have compiled a comprehensive information package focusing on the following themes: adaptation policy, impacts of climate change including economic impacts, regional adaptation strategies, climate and flood risks in regions and sea areas, and the availability of scientific data. This report consists of two parts. Part 1 of the report examines the work carried out on adaptation in Finland and internationally since 2005, emphasising the directions and priorities of recent research results. The possibilities of adaptation governance are examined through examples, such as how adaptations steering is organised in of the United Kingdom. We also examine other examples and describe the Canadian Climate Change Adaptation Platform (CCAP) model. We apply current information to describe the economic impacts of climate change and highlight the related needs for further information. With regard to regional climate strategy work, we examine the status of adaptation plans by region and the status of the Sámi in national adaptation work. In part 2 of the report, we have collected information on the temporal and local impacts of climate change and compiled extensive tables on changes in weather, climate and marine factors for each of Finland's current regions, the autonomous Åland Islands and five sea areas, the eastern Gulf of Finland, the western Gulf of Finland, the Archipelago Sea, the Bothnian Sea and the Bay of Bothnia. As regards changes in weather and climate factors, the changes already observed in 1991-2020 are examined compared to 1981-2010 and future changes until 2050 are described. For weather and climate factors, we examine average temperature, precipitation, thermal season duration, highest and lowest temperatures per day, the number of frost days, the depth and prevalence of snow, the intensity of heavy rainfall, relative humidity, wind speed, and the amount of frost per season (winter, spring, summer, autumn). Flood risks, i.e. water system floods, run-off water floods and sea water floods, are discussed from the perspective of catchment areas by region. The impacts of floods on the sea in terms of pollution are also assessed by sea area, especially for coastal areas. With regard to marine change factors, we examine surface temperature, salinity, medium water level, sea flood risk, waves, and sea ice. We also describe combined risks towards sea areas. With this report, we demonstrate what is known about climate change adaptation, what is not, and what calls for particular attention. The results can be utilised to strengthen Finland's climate policy so that the implementation of climate change adaptation is strengthened alongside climate change mitigation efforts. In practice, the report serves the reform of the National Climate Change Adaptation Plan and the development of steering measures for adaptation to climate change both nationally and regionally. Due to its scale, the report also serves e.g. the United Nations’ aim of protecting marine life in the Baltic Sea and the national implementation of the EU strategy for adaptation to climate change. As a whole, the implementation of adaptation policy in Finland must be speeded up swiftly in order to achieve the objectives set and ensure sufficient progress in adaptation in different sectors. The development of binding regulation and the systematic evaluation, monitoring and support of voluntary measures play a key role.
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Event-Triggered Adaptive Robust Control for Lateral Stability of Steer-by-Wire Vehicles with Abrupt Nonlinear Faults. SAE International, July 2022. http://dx.doi.org/10.4271/2022-01-5056.

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Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the extraordinary ability in coping with the issue of nonlinear, is applied to deal with the challenge of the changing longitudinal velocity. The output of the upper controller can be calculated by a parallel distributed compensation (PDC) scheme. Then an event-triggered adaptive fault-tolerant lower controller (ET-AFTC) is proposed to drive the whole SBW system driving the desired steering angle offered by the upper controller with fewer communication resources and strong robustness. By employing a backstepping technique, the tracking performance is improved. The dynamic surface control (DSC) approach is used to avoid the problem of repeated differentiations, and Nussbaum function is adopted to overcome the difficulty of unknown nonlinear control gain. Both the stability of the upper and lower controllers can be guaranteed by Lyapunov functions. Finally, the simulations of Matlab/Simulink are given to show that the proposed control strategy is effectively able to deal with the abrupt nonlinear fault via less communication resources and perform better in ensuring the yaw stability of the vehicle.
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