• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.55-72
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• 2017

Autonomous Vehicles(AV) are considered as an alternative to solve various social problems. Many researches which are related to developing technologies and AV operations have been conducted vastly and on-going. However, there seem to be little studies on various influences of AI algorithm on driving installed in AV. This study aims to examine the impacts of the ethical decisions made by Utilitarianism-based AI in AV when the oncoming car crossed over the central line. It establishes scenarios about situation of encroaching a central line and analyzes traffic impacts of ethical decision made by AV. According to the results of the analyses, as th accident occurs, overall speed of traffic decrease. There is a negative impact on the traffic flow when AV made an Utilitarian-based ethical decision by changing the lane. However, when AV choose to collide head-on, there is a positive effect to relieve traffic flow with an assistance of CACC, equipped.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.347-350
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• 2006

Maritime and Ocean Engineering Research Institute (MOERI), a branch of KORDI, has designed and manufactured a model of an autonomous underwater vehicle (AUV) named ISiMI(Integrated Submergible for Intelligent Mission Implementation). ISiMI is an AUV platform to satisfy the various needs of experimental test required for development of challenging technologies newly investigated in the field of underwater robot; control and navigational algorithms and software architectures. The main design goal of ISiMI AUV is downsizing which will reduce substantially the operating cost compared to other vehicles previously developed in KORDI such as VORAM or DUSAUV. As a result of design and manufacturing process, ISiMI is implemented to be 1.2m in length, 0.17m in diameter and weigh 20 kg in air. A series of tank test is conducted to verify the basic functions of ISiMI in the Ocean Engineering Basin of MOERI, which includes manual control with R/F link, auto depth, auto heading control and a final approach control for underwater docking. This paper describes the implementation of ISiMI system and the experimental results to verify the function of ISiMi as a test-bed AUV platform.

• Journal of Biosystems Engineering
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• v.34 no.4
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• pp.278-285
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• 2009

Navigation system is applied in variety of fields including the simple location positioning, autopilot navigation of unmanned robot tractor, autonomous guidance systems for agricultural vehicles, construction of large field works that require high precision and map making process. Particularly utilization of GPS (Global Positioning System) is very common in the present navigation system. This study introduces a navigation system for autonomous field robot that travels to the pre-input path using GPS information. Performance of the GPS- based navigation is highly depended on its receiving rate because GPS receivers do not acquire any navigation information in the period between the refresh intervals. So this study presents an algorithm that improves an accuracy of the navigation by estimation the positional information during the blind period of a low rate GPS receiver. In fact the algorithm calculated the robot's heading in a 50 Hz rate, so the blind period of an 1 Hz GPS receiver is extensively covered. Consequently implementation of the algorithm to the GPS based navigation showed an improvement in guidance accuracy. The conventional field robot directly carried an expensive control computer and sensors onboard, therefore the miniaturization and weight reduction of the robot was limited. In this paper, the field robot carried only communication equipments such as GPS module, normal RC receiver, and bluetooth modem. This enabled the field robot to be built in an economic cost and miniature size.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.6
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• pp.535-542
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• 2011

The Global Navigation Satellite System(GNSS) is being utilized in numerous applications. The research for autonomous guided vehicles(AGVs) using precise positioning of GNSS is in progress. GNSS based AGVs is useful for setting driving path. This AGV system is more efficient than the previous one. Escipecially, the obstacle is positioned the driving path. Previcious AGVs which follow marker or wires laid out on the road have to stop the front of obstacle. But GNSS based AGVS can continuously drive using obstacle avoidance. In this paper, we developed collision avoidance system for GNSS based AGV using laser scanner and collision avoidance path setting algorithm. And we analyzed the developed system.

• Journal of IKEEE
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• v.24 no.1
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• pp.232-237
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• 2020

In this paper, we propose an efficient sensor fusion method for autonomous vehicle recognition and distance measurement. Typical sensors used in autonomous vehicles are radar, lidar and camera. Among these, the lidar sensor is used to create a map around the vehicle. This has the disadvantage, however, of poor performance in weather conditions and the high cost of the sensor. In this paper, to compensate for these shortcomings, the distance is measured with a radar sensor that is relatively inexpensive and free of snow, rain and fog. The camera sensor with excellent object recognition rate is fused to measure object distance. The converged video is transmitted to a smartphone in real time through an IP server and can be used for an autonomous driving assistance system that determines the current vehicle situation from inside and outside.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.10
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• pp.44-49
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• 2021

Seats in autonomous vehicles must be able to rotate to fully utilize the interior space. Generally, ultra-high strength steel is used for the rotation module because it should have high strength and high rigidity. In addition, the rotating parts are difficult to form because they have complex shapes. In this study, the upper plate of the rotating module, whose complex shape makes it difficult to form, was formed by applying the hot stamping method. The drawing method and the form-drawing method, which are generally used to form components of complex shapes, were compared. We showed that the form-drawing method increased the degree of freedom of the material flow to improve the formability, thus enabling the forming of the plate. In addition, the die and blank shapes were found to be important factors in determining the success of the hot stamping. The validity of the analysis results was confirmed through forming analysis and experiments.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1131-1142
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• 2018

The autonomous vehicles are being developed and operated widely because of the advantages of reducing the traffic accident and saving time and cost for driving. The vehicle localization is an essential component for autonomous vehicle operation. In this paper, localization algorithm based on sensor fusion is developed for cost-effective localization using in-vehicle sensors, GNSS, an image sensor and reference images that made in advance. Information of the reference images can overcome the limitation of the low positioning accuracy that occurs when only the sensor information is used. And it also can acquire estimated result of stable position even if the car is located in the satellite signal blockage area. The particle filter is used for sensor fusion that can reflect various probability density distributions of individual sensors. For evaluating the performance of the algorithm, a data acquisition system was built and the driving data and the reference image data were acquired. Finally, we can verify that the vehicle positioning can be performed with an accuracy of about 0.7 m when the route image and the reference image information are integrated with the route path having a relatively large error by the satellite sensor.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.157-163
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• 2019

The LiDAR sensor, which is widely regarded as one of the most important sensors, has recently undergone active commercialization owing to the significant growth in the production of ADAS and autonomous vehicle components. The LiDAR sensor technology involves radiating a laser beam at a particular angle and acquiring a three-dimensional image by measuring the lapsed time of the laser beam that has returned after being reflected. The LiDAR sensor has been incorporated and utilized in various devices such as drones and robots. This study focuses on object detection and recognition by employing sensor fusion. Object detection and recognition can be executed as a single function by incorporating sensors capable of recognition, such as image sensors, optical sensors, and propagation sensors. However, a single sensor has limitations with respect to object detection and recognition, and such limitations can be overcome by employing multiple sensors. In this paper, the performance of an eight-channel scanning LiDAR was evaluated and an object detection algorithm based on it was implemented. Furthermore, object detection characteristics during daytime and nighttime in a real road environment were verified. Obtained experimental results corroborate that an excellent detection performance of 92.87% can be achieved.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.29-36
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• 2019

Unmanned Autonomous Vehicle's driving road in the national defense includes not only paved roads, but also unpaved roads which have rough and unexpected changes. This Unmanned Autonomous Vehicles monitor and recon rugged or remote areas, and defend own position, they frequently encounter environments roads of various and unpredictable. Thus, they need additional learning to drive in this environment, we propose a Additional Learning Nearest Neighbor (ALNN) which is modified from Approximate Nearest Neighbor to allow for quick learning while avoiding the 'Forgetting' problem. In addition, since the Execution speed of the ALNN algorithm decreases as the learning data accumulates, we also propose a solution to this problem using GPU parallel processing based on OpenGL Shader Language. The ALNN based on GPU algorithm can be used in the field of national defense and other similar fields, which require frequent and quick application of additional learning in real-time without affecting the existing learning data.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.521-526
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• 2020

In this paper, we propose a design method and process for hybrid V2X communication platform that combines WAVE communication and LTE-V2X communication which are C-ITS communication protocols for vehicle environments and Legacy LTE communication which is a commercial mobile communication for evaluating the autonomous platooning platform of commercial vehicles. For a safe and efficient autonomous platooning platform, an low-latency communication function based on C-ITS communication is required, and to control it, commercial communication functions such as Legacy LTE, which can be connected at all times, are required. In order to evaluate such a system, the evaluation equipment must have the same level of communication performance or higher. The main design contents presented in this paper will be applied to the implementation of hybrid V2X terminals for functional evaluation.