• Journal of Auto-vehicle Safety Association
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• v.10 no.2
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• pp.29-35
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• 2018

This paper presents a quantitative evaluation method and result of moving vehicle perception using automotive radar. It is also important to analyze the accuracy of the perception algorithm quantitatively as well as to accurately percept nearby moving vehicles for safe and efficient autonomous driving. In this study, accuracy of the automotive radar-based perception algorithm which is developed based on interacting multiple model (IMM) has been verified via vehicle tests on real roads. In order to obtain experimental data for quantitative evaluation, Long Range Radar (LRR) has been mounted on the front of the ego vehicle and Short Range Radar (SRR) has been mounted on the rear side of both sides. RT-range has been installed on the ego vehicle and the target vehicle to simultaneously collect reference data on the states of the two vehicles. The experimental data is acquired in various relative positions and velocity, and the accuracy of the algorithm has been analyzed according to relative position and velocity. Quantitative analysis is conducted on relative position, relative heading angle, absolute velocity, and yaw rate of each vehicle.

• Journal of Ocean Engineering and Technology
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• v.33 no.6
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• pp.620-626
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• 2019

With the development of robot technology, the expectation of autonomous mission operations has increased, and the research on robot control architectures and mission planners has continued. A scalable and robust control architecture is required for unmanned surface vehicles (USVs) to perform a variety of tasks, such as surveillance, reconnaissance, and search and rescue operations, in unstructured and time-varying maritime environments. In this paper, we propose a robot control architecture along with a new utility function that can be extended to various applications for USVs. Also, an additional structure is proposed to reflect the operator's command and improve the performance of the autonomous mission. The proposed architecture was developed using a robot operating system (ROS), and the performance and feasibility of the architecture were verified through simulations.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.387-392
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• 2014

Now a days, there are various application functions to transmit from vehicles to the Internet and vice versa. And the communication can be operated through a roadside infrastructure including with possible use of routing protocols. Specifically, autonomous vehicles for remote driving and monitoring requires transmitting of high depth of multimedia such as video. Especially in a populated urban area, an efficient network is vital because of handling a great amount of the data. Therefore, in this paper, efficient network topology for a crossroad in urban area is suggested by performance evaluation of vehicular networks using a wireless LAN and a routing protocol. For the performance evaluation, various vehicular network topologies are designed and simulated in OPNet simulator.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1879-1886
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• 2016

In this paper, we propose a real-time recognition algorithm of lanes, stop lines and speed bumps on roads for autonomous vehicles. First, we generate a top-view using the image transmitted from a camera that is installed to see the front of a vehicle. To speed up the processing, we simplify the mapping algorithm in constructing a top-view wherein the region of interest (ROI) is concerned. The features of lanes, stop lines and speed bumps, which are composed of lines, are searched in the edge image of the top-view, then followed by labeling and clustering specialized to detect straight lines. The width of lines, distances from the center of a vehicle, and curvature of each cluster are considered to select final candidates. We verify the proposed algorithm on real roads using the commercial car (KIA K7) which is converted into an autonomous vehicle.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.3
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• pp.243-251
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• 2016

Autonomous Underwater Vehicles (AUVs) generally work in complex marine environments. Any fault in AUVs may cause significant losses. Thus, system reliability and automatic fault diagnosis are important. To address the actuator failure of AUVs, a fault diagnosis method based on the Gaussian particle filter is proposed in this study. Six free-space motion equation mathematical models are established in accordance with the actuator configuration of AUVs. The value of the control (moment) loss parameter is adopted on the basis of these models to represent underwater vehicle malfunction, and an actuator failure model is established. An improved Gaussian particle filtering algorithm is proposed and is used to estimate the AUV failure model and motion state. Bayes algorithm is employed to perform robot fault detection. The sliding window method is adopted for fault magnitude estimation. The feasibility and validity of the proposed method are verified through simulation experiments and experimental data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.1
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• pp.70-76
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• 2013

Recently, the performance and function of electrical and electronic system in automotive vehicles is developing at a rapid rate with the advancement of IT technologies. Combined together with micro-controller and sensor technologies, the Vehicle Smart System (VSS) being developed to improve driver's convenience and comfort has been employed to a variety of applications. In addition to the convenience system, the Auto-parking Assistance System (AAS) that is now attracting a new attention has been already applied to some vehicles, but it is currently limited to luxury car models only. In this paper, we present a fuzzy controller that enables autonomous parking assistance without the AAS. The controller can perform the assistance with information provided from moving status, current position and steering angle as one is able to park a car based on his/her experience and knowledge for driving and parking. We have evaluated its performance of the proposed controller by simulation and tested the excellence of the controller by building a model vehicle embedded with the micro-controllers.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1053-1060
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• 2016

As location recognition for autonomous vehicles develops, the need for a precise map for autonomous driving has increased. A precise map must be built based upon accurate position. Recent studies have accelerated research in this area by using various sensors that calculate the accurate position by comparing and recognizing objects around the roads. However, application of such methods is limited because these studies only take objects with significant verticality into consideration. Thus, new research is needed to overcome the limitations: a method that is not constrained by the existence of certain types of surrounding objects shall be proposed. Most roads contain road marking information, such as lanes, direction signs, and pedestrian crossings. Such information on the road surface is a valuable resource for building a precise map. This paper proposes a method of building a precise map by using road marking information.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.513-517
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• 2006

Autonomous Underwater Vehicles plays specific role in underwater investigation. Generally, this kind of vehicles will move along a planned path for sea bottom or underwater installations inspections, search for mineral deposits along shelves, seeking lost items including bottom mines or for hydrographic measurements. A crucial barrier for it remains the possibility of precise determination of their underwater position. Commonly used radionavigation systems do not work in such circumstances or do not guarantee the required accuracies. In the paper some new solution is proposed on the assumption that it is possible to increase the precision by certain processing of a combination of measurements conducted by means of different techniques. Objective of the paper is the idea of navigation of AUV which consists of two phases: firstly a trip of AUV along pre-planned route and after that postprocessed transformation of collected data in post-processing mode. During the processing of collected data the modern adjustment methods have been applied, mainly estimation by means of least squares and M-estimation. Application of these methods should be associated with the measuring and geometric conditions of navigational tasks and thus suited for specific scientific and technical problems of underwater navigation. The first results of computer aided investigation will be presented and the basic scope of these application and possible development directions will be indicated also. The paper is prepared as an partial results of the works carried out within a framework of the research Project: 'Improvement of the Precise Underwater Vehicle Navigation Methods' financed by the Polish Ministry of Education and Science (No 0 T00A 012 25).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.266-273
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• 2019

The efficiency and effectiveness of mission performance can be greatly changed according to the operating conditions such as the number of manned aircraft, flight altitude, and so on, in performing search and reconnaissance missions using a large number of small reconnaissance unmanned aerial vehicles. However, it is not easy to determine which operating conditions are most reasonable. Therefore, in this study, we developed an unmanned airplane flight simulation that can detect and identify the target while avoiding collision according to autonomous flight, suggesting a way to derive operating conditions when operating a large number of unmanned aerial vehicles.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.95-101
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• 2023

As the popularization of autonomous vehicles is anticipated, it is expected that the variety of passenger postures will diversify. However, the current vehicle safety system is expected to be inadequate for accommodating these diverse passenger postures, particularly in reclined positions where severe injuries have been reported in frontal collisions. Therefore, it is necessary to investigate the biomechanical responses and tolerances of occupants in reclined postures. In this study, the behavior and injuries of a Hybrid-III dummy model in a reclined position are analyzed through frontal collision sled simulations equipped with the semi-rigid seat provided by the previous study, three-point safety belt with pretensioner and load limiter, and airbag models. The results are evaluated by comparing thouse reponses with post-mortem human surrogate (PMHS) data, and the findings are expected to be applicable to the basic design of a new restraint system suitable for various postures in autonomous vehicles.