• Journal of Drive and Control
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• v.12 no.3
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• pp.36-43
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• 2015

An autonomous vehicle control algorithm based on Ackerman Geometry is known to be reliable in low tire slip situation. However, vehicles at high speed make lateral errors due to high tire slip. In this paper, considering the tire slip of vehicles, the steering angle is determined based on the Ackerman Geometry and is supplemented tire slip angle by the Stanley steering algorithm. In addition, to prevent the tire slip, the algorithm, which restricts steering if a certain level of slip occurs, is used to reduce the lateral error. While many studies have been extended to include vehicle slip, studies also need to be carried out on the tire slip depending on hardware performance. The control algorithm of autonomous vehicles is compensated considering the sensor noise and the performance of steering actuator. Through the various simulations, it was found that the performance of steering actuator was the key factor affecting the performance of autonomous driving. Also, it was verified that the usefulness of steering algorithm considering the tire slip and performance of steering actuator.

• Journal of Advanced Navigation Technology
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• v.23 no.4
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• pp.296-301
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• 2019

Artificial intelligence is closely linked to our real lives, leading innovation in various fields. Especially, as a means of transportation possessing artificial intelligence, autonomous unmanned vehicles are actively researched and are expected to be put into practical use soon. Autonomous cars and autonomous unmanned aerial vehicles are required to equip accurate navigation system so that they can find out their present position and move to their destination. At present, the navigation of transportation that we operate is mostly dependent on GPS. However, GPS is vulnerable to external intereference. In fact, since 2010, North Korea has jammed GPS several times, causing serious disruptions to mobile communications and aircraft operations. Therefore, in order to ensure safety in the operation of the autonomous unmanned vehicles and to prevent serious accidents caused by the intereference, rapid situation judgment and countermeasure are required. In this paper, based on big data and machine learning technology, we propose a countermeasure system for GPS interference that supports decision making by applying John Boyd's OODA loop cycle (detection - direction setting - determination - action).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.7-14
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• 2021

By changing the bulky monolithic services architecture to a microservices-based architecture, industries are managing the rising complexity of Autonomous Vehicles. However, the underlying communication mechanisms for the utilization and distribution of these microservices are incapable of fulfilling the requirements of the futuristic AV, because of the stringent latency requirements along with intermittent and short-lived connectivity issues. This paper proposes to tackle these challenges by employing the revolutionary information-centric networking (ICN) paradigm as an underlying communication architecture. This paper argues that a microservice approach to building autonomous vehicle systems should utilize ICN to achieve effective service utilization, efficient distribution, and uniform service discovery. This research claims that the vision of an information-centric microservices will help to focus on research that can fill in current communication gaps preventing more effective, and lightweight autonomous vehicle services and communication protocols.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.464-470
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• 2021

Automobiles have been used as simple means of transportation, but recently, as automobiles are rapidly becoming intelligent and smart, and automobile preferences are increasing, research on IT technology convergence is underway, requiring basic high-performance functions such as driver's convenience and safety. As a result, autonomous driving and semi-autonomous vehicles are developed, and these technologies sometimes deviate from lanes due to environmental problems, situations that cannot be judged by autonomous vehicles, and lane detectors may not recognize lanes. In order to improve the performance of lane departure from the lane detection system of autonomous vehicles, which is such a problem, this paper uses fast recognition, which is a characteristic of YOLO(You only look once), and is affected by the surrounding environment using CSI-Camera. We propose a lane detection system that recognizes the situation and collects driving data to extract the region of interest.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1117-1123
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• 2021

Object recognition is to identify the location and class of a specific object by analyzing the given image when a specific image is input. One of the fields in which object recognition technology is actively applied in recent years is autonomous vehicles, and this paper describes the trend of image-based object recognition artificial intelligence technology in autonomous vehicles. The image-based object detection algorithm has recently been narrowed down to two methods (a single-step detection method and a two-step detection method), and we will analyze and organize them around this. The advantages and disadvantages of the two detection methods are analyzed and presented, and the YOLO/SSD algorithm belonging to the single-step detection method and the R-CNN/Faster R-CNN algorithm belonging to the two-step detection method are analyzed and described. This will allow the algorithms suitable for each object recognition application required for autonomous driving to be selectively selected and R&D.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.161-172
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• 2023

Autonomous driving vehicles recognize the surroundings through various sensors mounted on the vehicle and control the vehicle based on the collected information. The level of autonomous driving technology is improving due to the development of sensor technology and algorithms that process collected data, but the implementation of perfect autonomous driving technology has not been achieved. To overcome these limitations, through autonomous cooperative driving centered on infrastructure. In this study, developed a position correction sign that provides a reference for positioning of autonomous vehicles. First of all, an analysis was performed on the current status of positioning technology for autonomous driving. And measure the number of point clouds for the 1st sample consisting of two square reflective surfaces and 2nd sample that increased the vertical length of each reflective surface. Experimental results show that both primary and secondary products are installed at least 15 m apart It could be recognized as a sensor, and it was confirmed that the secondary production that increased the length of the top and bottom had a higher number of point clouds than the primary production and better expressed the shape of the facility.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.107-112
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• 2003

In general, the dynamics of autonomous underwater vehicles(AUVs) are highly nonlinear and time-varying, and the hydrodynamic coefficients of vehicles are hard to estimate accurately because of the variations of these coefficients with different navigation conditions. For this reason, in this paper, the control gain function is assumed to be unknown and the exogenous input term is assumed to be unbounded, although it still satisfies certain restrict condition. And these two kinds of wild assumptions have been seldom handled simultaneously in one system because of the difficulty of stability analysis. Under the above two relaxed assumptions, a robust neural network control scheme is presented for autonomous diving control of an AUV, and can guarantee that all the signals in the closed-loop system are UUB (uniformly ultimately bounded). Some practical features of the proposed control law are also discussed.

• Journal of Power System Engineering
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• v.20 no.1
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• pp.24-29
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• 2016

Remotely operated vehicles or autonomous underwater vehicles have been used for exploiting seabed natural resources. In this study, the autonomous underwater vehicle of hovering type(HAUV) is developed to observe underwater objects in close distance. A dynamic model with six degrees of freedom is established, capturing the motion characteristics of the HAUV. The equations of motion are generated for the dynamic control simulation of the HAUV. The added mass, drag and lift forces are included in the computer model. Computational fluid dynamics simulation is carried out using this computer model. The drag coefficients are produced from the CFD.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.1-7
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• 2012

This paper deals with the global path planning problem for AUVs (autonomous underwater vehicles) in a tidal current field. The previous researches in the field were unsuccessful at simultaneously addressing the two issues of obstacle avoidance and tidal current-based optimization. The use of a genetic algorithm is proposed in this paper to move past this limitation and solve both issues at once. Simulation results showed that the genetic algorithm could be applied to generate an optimal path in the field of a tidal current with multiple obstacles.

• International Journal of Ocean System Engineering
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• v.2 no.3
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• pp.139-150
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• 2012

This paper presents an improved guidance algorithm for autonomous underwater vehicles (AUV) in 3D space for generating smoother vehicle turn during the course change at the way-points. The way-point guidance by the line-of-sight (LOS) method has been modified for correcting the reference angles to achieve minimal calculation and smoother transition at the way-points. The algorithm has two phases in which the first phase brings the vehicle to converge to a distance threshold point on the line segment connecting the first two way-points and the next phase generates an angular path with smoother transition at the way-points. Then the desired angles are calculated from the reference and correction angles. The path points are regularly parameterized in the spherical coordinates and mapped to the Cartesian coordinates. The proposed algorithm is found to be simple and can be used for real time implementation. The details of the algorithm and simulation results are presented.