• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.176-190
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• 2002

According as vehicles increases, system such as Advanced Drivers Assistance System(ADAS ) to inform forward situation to driver is required. In this paper, we proposes method to detect forward vehicles and lane from sequential color images by basis process to inform forward situation to driver. We detect a front vehicle using that shadow area exists on part under vehicles and that road area occupies many parts even if road traffic is confused. We detect lane information using that lane part is white order by reverse characteristic of shadow area. This method shows good result in case road is confused or there is direction indication to road. HSV color space is selected for color modeling. This method uses saturation component and value component in HSV color model to detect vehicles and lane. It uses statistics features of HSV component and position to know whether detected vehicles area is vehicles such as vehicles previous frame. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and Present the results such as processing time, accuracy and vehicles detection against the images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.1-8
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• 2017

This paper presents the development of an adaptive cruise control (ACC) system, which is one of the typical advanced driver assist systems, for 4-wheel drive hybrid in-wheel electric vehicles. The front wheels of the vehicle are driven by a combustion engine, while its rear wheels are driven by in-wheel motors. This paper proposes an adaptive cruise control system which takes advantage of the unique driveline configuration presented herein, while the proposed power distribution algorithm guarantees its tracking performance and fuel efficiency at the same time. With the proposed algorithm, the vehicle is driven only by the engine in normal situations, while the in-wheel motors are used to distribute the power to the rear wheels if the tracking performance decreases. This paper also presents the modeling of the in-wheel motors, hybrid in-wheel driveline, and integrated ACC control system based on a commercial high-precision vehicle dynamics model. The simulation results obtained with the model are presented to confirm the performance of the proposed algorithm.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.319-324
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• 2016

In the case of robot and Argument Reality applications using a camera in environments, a technology to estimate planes is a very important technology. A RGB-D camera can get a three-dimensional measurement data even in a flat which has no information of the texture of the plane;, however, there is an enormous amount of computation in order to process the point-cloud data of the image. Furthermore, it could not know the number of planes that are currently observed as an advance, also, there is an additional operation required to estimate a three dimensional plane. In this paper, we proposed the real-time method that decides the number of planes automatically and estimates the three dimensional plane by using the continuous data of an RGB-D camera. As experimental results, the proposed method showed an improvement of approximately 22 times faster speed compared to processing the entire data.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.452-459
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• 2019

In order for an autonomous vehicle to be commercialized, it is necessary to conduct a safety test for every aspect. Considering the implementation of the autonomous vehicles technologies to the highest level, it is necessary to analyze the possible scenarios in the most complex environment as in the urban area. It should be confirmed whether autonomous vehicles can be operated with conventional traffic signal environment. It is also required to confirm the ability of autonomous vehicles in interacting with other vehicles, and coping with possible accidents on the road. In this study, the evaluation factors of autonomous vehicles in the road environment are selected by referring to the other evaluation protocols like ADAS. Study result would be reflected in establishing the autonomous vehicle evaluation method for different test environment along with various technology implementation level.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.231-236
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• 2016

Currently, a traffic monitoring service using a surveillance camera is provided through internet. In general, if the user points a certain location on a map, then this service shows the real-time image of the camera where it is mounted. In this paper, we proposed the intuitive surveillance monitoring system which displays a real-time camera image on the map by warping with bird's-eye view and with the top of image as the north. In order to robustly estimate the road plane using camera image, we used the motion vectors which can be detected to changes in brightness. We applied a re-adjustment process to have the same directivity with a map and presented a user-friendly interface that can be displayed on the map. In the experiment, the proposed method was presented as the result of warping image that the user can easily perceive like a map.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.94-102
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• 2012

Recently entered into an aging socity as the number of elderly drivers is increasing. Traffic accidents of elderly drivers are caused by driver inattentions such as poor vehicle control due to aging, visual information retrieval problems caused by presbyopia, and objects identifying problems caused by low contrast sensitivity. In this paper, detection method of ROIs on the road is proposed. The proposed method creates the saliency map to detect the candidate ROIs from the input image. And, the input image is segmented to obtain the ROIs boundary. Finally, selective visual attention regions are detected according to the presence or absence of a segmented region with saliency pixels. Experimental results from a variety of outdoor environmental conditions, the proposed method presented a fast object detection and a high detection rate.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.330-330
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• 2016

The quantification of dry season evaporation in regions, where the magnitude of dry season flows is key to the regional water supply, is essential for good water management. Also, tree transpiration has a significant role in the water balance of a catchment whenever it is tree populated, especially in water limited environments. Such is the case in the Middle Mountains of Nepal where dry season flows play a significant role in downstream water provisioning and their proper functioning is key to the welfare of millions of people. This research seeks to study the transpiration of a pine forest stand in the Jikhu Khola Watershed in the Middle Mountains of Nepal. To the author's knowledge, no single study has been made so far to estimate the dry season evaporation from the planted forest stand in the Middle Mountains of Nepal. The study was carried out in planted pine forest embedded within the Jikhu Khola Catchment. Field campaigns of sap flow measurements were carried out from September, 2010 to February, 2011 in the selected plot of 15*15m dimension, to characterize dry season evaporation. This was done by measuring sap fluxes and sapwood areas over the six trees of different Diameter at Breast Height (DBH) classes. The sap flux was assessed using Granier's thermal dissipation probe (TDP) technique while sapwood area was determined using several incremental core(s) taken with a Pressler borer and immediately dyeing with methyl orange for estimating the actual depth of sapwood area. Transpiration of the plot was estimated by considering the contribution of each tree class. For this purpose, sap flux density, sapwood area and the proportion of total canopy area were determined for each tree class of the selected plot. From these data, hourly and diurnal transpiration rates for the plot were calculated for experimental period. Finally, Cienciala model was parameterized using the data recorded by the ADAS and other terrain data collected in the field. The calibrated model allowed the extrapolation of Sap flux density (v) over a six month period, from September 2010 to February 2011. The model given sap flux density was validated with the measured sap flux density from Grainier method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.79-94
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• 2021

A GNSS receiver installed in autonomous vehicles is the most essential device for its navigation. However, if an intentional jamming signal is generated, there is a risk of exposure to an accident risk due to deterioration of the GNSS sensor's performance. Research is required to prevent this, and accordingly, a jamming generating device must be provided. However, according to the provisions of the law related to jamming, this is illegal. In this paper, we implement an in-vehicle jamming device that complies with the provisions of the law and does not affect the surrounding GNSS sensors. Driving simulation is used to evaluate the performance of the GNSS algorithm, and the malfunction of autonomous vehicles occurring in the interference environment and data errors output from the GNSS sensor are analyzed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1088-1095
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• 2019

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

• 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.