• Journal of Drive and Control
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• v.20 no.3
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• pp.35-41
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• 2023

Radish and Chinese cabbage are the most produced and consumed vegetables in Korea. The mechanization of harvesting operations is necessary to minimize the need for manual labor. This study to develop and evaluate the performance of a multi-purpose driving platform that can apply modular Radish and Chinese cabbage harvesting devices. The multi-purpose driving platform consisted of driving, device control, engine, hydraulic, harvesting, conveying, and loading part. Radish and Chinese cabbage harvesting conducted using the multi-purpose driving platform each harvesting module. The performance of the multi-purpose driving platform was evaluated the field efficiency and loss rate. The total Radish harvesting operation time 34.3 min., including 28.8 min., of harvesting time, 1.9 min., of turning time, and 3.6 min., of replacement time of bulk bag. During Radish harvesting, the field efficiency and average loss rate of the multi-purpose driving platform were 2.0 hr/10a and 3.1 %. Chinese cabbage harvesting operation 49.3 min., including 26.6 min., of harvesting time, 4.6 min., of turning time, and 18.1 min., of replacement time of bulk bag. During Chinese cabbage harvesting, the field efficiency and average loss rate of the multi-purpose driving platform 2.1 hr/10a and 0.1 %. Performance evaluation of the multi-purpose driving platform that harvesting work was possible by installing Radish and Chinese cabbage harvest modules. Performance analysis through harvest performance evaluation in various Radish and Chinese cabbage cultivation environments is necessary.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.7
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• pp.115-121
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• 1996

Multi-axes driving system is more suitable for FMS(Flexible Manufacturing System) compared with a conventional single-azis driving system. It has some merits such as flexibility in operation, improvement of net working rate, maintenance free because of no gear train, etc. However, studies on position synchronous control for high precision in the multi-axes driving system are not enough. In this paper, a new method of position synchronous control is suggested in order to apply to the multi- axes driving system. The proposed method is structured very simply using speed and position controller based on PID control law. Especially, the position controller is designed to keep position error to minimize by controlling either speed of two motors. The effectiveness of the proposed method is successfully confirmed through several experiments.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.375-382
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• 2007

The multi-driver off-road vehicle drive-line consists of many components, with close connections among them. In order to design and analyze the drive-line efficiently, a modular methodology should be taken. The aim of a modular approach to the modeling of complex systems is to support behavior analysis and simulation in an iterative and thus complex engineering process, by using encapsulated submodels of components and of their interfaces. Multi-driver off-road vehicles are comparatively complicated. The driving-line is an important core part to the vehicle, it has a significant contribution to the performance. Multi-driver off-road vehicles have complex driving-lines, so performance is heavily dependent on the driving-line. A typical off-road vehicle's driving-line system consists of a torque converter, transmission, transfer case and driving-axles, which transfers the power generated by the engine and distributes it effectively to the driving wheels according to the road condition. According to its main function, this paper proposes a modularized approach for design and evaluation of the vehicle's driving-line. It can be used to effectively estimate the performance of the driving-line during the concept design stage. Through an appropriate analysis and assessment method, an optimal design can be reached. This method has been applied to practical vehicle design, it can improve the design efficiency and is convenient to assess and validate the performance of a vehicle, especially of multi-driver off-road vehicles.

• Journal of Auto-vehicle Safety Association
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• v.8 no.4
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• pp.31-37
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• 2016

Since real road experiments have many restrictions, a multi-vehicle traffic simulator can be an effective tool to develop and evaluate fully automated driving systems. This paper presents multi-vehicle environment simulation tool to develop and evaluate motorway automated driving systems. The proposed simulation tool consists of following two main parts: surrounding vehicle model and environment sensor model. The surrounding vehicle model is designed to quickly generate rational complex traffic situations of motorway. The environment sensor model depicts uncertainty of environment sensor. As a result, various traffic situations with uncertainty of environment sensor can be proposed by the multi-vehicle environment simulation tool. An application to automated driving system has been conducted. A lane changing algorithm is evaluated by performance indexes from the multi-vehicle environment simulation tool.

• Journal of Auto-vehicle Safety Association
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• v.10 no.2
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• pp.50-55
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• 2018

Choosing automobile safety options is price-performance matter. The best fit options to buyer who has a certain driving habit are problem of MCDM (Multi Criteria Decision Making) because price of safety option, statistics of relating accident, consequence of accident, and driving habit are the multi criteria to be evaluated. In this paper, PROMETHEE-GAIA methodology is applied for solving this MCDM problem. The result shows that a different driving habit makes different choosing priority of safety options.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.582-587
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• 2004

Ultrasonic sensors are widely used in mobile robot applications to recognize external environments, because they are cheap, easy to use, and robust under varying lighting conditions. However, the recognition of objects using a ultrasonic sensor is not so easy due to its characteristics such as narrow beam width and no reflected signal from a inclined object. As one of the alternatives to resolve these problems, use of multiple sensors has been studied. A sequential driving system needs a long measurement time and does not take advantage of multiple sensors. Simultaneous and pulse coding driving system of ultrasonic sensor array cannot measure short distance as the length of the code becomes long. This problem can be resolved by multi-frequency driving of ultrasonic sensors, which allows multi-sensors to be fired simultaneously and adjacent objects to be distinguished. Accordingly, this paper presents a simultaneous and multi-frequency driving system for an ultrasonic sensor array for object recognition. The proposed system is designed and implemented using a DSP and FPGA. A micro-controller board is made using a DSP, Polaroid 6500 ranging modules are modified for firing the multi-frequency signals, and a 5-channel frequency modulated signal generating board is made using a FPGA. To verify the proposed method, experiments were conducted in an environment with overlapping signals, and the flight distances for each sensor were obtained from filtering of the received overlapping signals and calculation of the time-of-flights.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1048-1051
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• 1996

In this paper, we present real-time S/W architecture and techniques such as real-time scheduling, synchronization, and etc. for implementation of a real-time control system for driving multi-motors. Simulation shows feasibility of real-time S/W techniques presented here.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.51-63
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• 2022

Convoy driving is one of the technologies of multi-vehicle cooperation driving along with platoon driving. All over the world, research on vehicle control mechanisms to maintain vehicle formation during convoy driving convoy driving has been actively conducted and in Europe's Autonet 2030 project has developed and demonstrated convoy driving services for highways. But, even the concept of convoy driving is still insufficient in Korea. Therefore, in this study, the concept of convoy driving service was established and scenarios and communication messages for service application on urban roads were developed. And its effectiveness was verified through simulation analysis. As a result of comparing and analyzing individual vehicle cooperative driving and convoy driving for the blind spot support service and dilemma zone safety support service, which are representative V2I cooperative driving services on urban roads, the number of conflicts(indicator of traffic safety) and delays and stops(indicator of traffic efficiency) are significantly improved in convoy driving compared to individual vehicle cooperative driving.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.245-254
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• 2022

Sensor dataset for autonomous driving is one of the essential components as the deep learning approaches are widely used. However, most driving datasets are focused on typical environments such as sunny or cloudy. In addition, most datasets deal with color images and lidar. In this paper, we propose a driving dataset with multi-spectral images and lidar in adverse weather conditions such as snowy, rainy, smoky, and dusty. The proposed data acquisition system has 4 types of cameras (color, near-infrared, shortwave, thermal), 1 lidar, 2 radars, and a navigation sensor. Our dataset is the first dataset that handles multi-spectral cameras in adverse weather conditions. The Proposed dataset is annotated as 2D semantic labels, 3D semantic labels, and 2D/3D bounding boxes. Many tasks are available on our dataset, for example, object detection and driveable region detection. We also present some experimental results on the adverse weather dataset.