• ETRI Journal
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• v.36 no.6
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• pp.968-978
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• 2014

Autonomous vehicle technology based on information technology and software will lead the automotive industry in the near future. Vehicle localization technology is a core expertise geared toward developing autonomous vehicles and will provide location information for control and decision. This paper proposes an effective vision-based localization technology to be applied to autonomous vehicles. In particular, the proposed technology makes use of numerical maps that are widely used in the field of geographic information systems and that have already been built in advance. Optimum vehicle ego-motion estimation and road marking feature extraction techniques are adopted and then combined by an extended Kalman filter and particle filter to make up the localization technology. The implementation results of this paper show remarkable results; namely, an 18 ms mean processing time and 10 cm location error. In addition, autonomous driving and parking are successfully completed with an unmanned vehicle within a $300m{\times}500m$ space.

• Information Systems Review
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• v.25 no.4
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• pp.113-130
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• 2023

Due to economic development and increasing gross national income, the number of automobiles continues to rise, leading to a serious issue of illegal parking due to limited road conditions and insufficient parking facilities. Illegal parking causes significant inconvenience and displeasure to people and can even result in accidents and loss of lives. The severity of accidents and their consequences, related to the growing number of vehicles and illegal parking, is escalating, particularly in the metropolitan areas. Consequently, efforts are being made to address this problem as a cause of social issues and come up with measures to reduce illegal parking. In particular, half of the public complaints in the metropolitan area are related to illegal parking, and the highest physical and human damage occurs in Gyeonggi. Thus, this study aims to use machine learning techniques based on data related to illegal parking in Suwon city, Gyeonggi, to categorize regional characteristics and propose effective measures to crack down on illegal parking. Additionally, practical, social, policy, and legal measures to decrease illegal parking in the metropolitan area are suggested. This study has academic significance in that it solved the problem of illegal parking, which is mentioned as one of the social problems that cause traffic congestion, by classifying regional characteristics using K-prototype, a machine learning algorithm. Furthermore, the results of this study contribute to practical and social aspects by providing measures to decrease illegal parking in the metropolitan area.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.1
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• pp.67-72
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• 2014

In this paper, we proposed A Study on Construction of Infrastructure for Handicapped Parking Areas Using RFID. This paper is Construction of the Handicapped Parking Areas infrastructure Using RFID with 900MHz band, and researched the optimal position of the tag attached on the vehicle and the location of RFID reader in order to raise the efficiency of RFID reader and the recognition rate by the handicapped vehicle. The result of research is shown the optimal position of RFID reader establishment when the height of RFID reader is 170cm in height and the angle of $80^{\circ}$ with the ground when the vehicle traveling direction of the antenna and the RFID reader when the surface and the angle of $90^{\circ}$ showed the best position RFID readers installed. Parking spaces for the disabled in accordance with these results the RFID readers installed and it works in conjunction with enforcement camera car tagged crackdown on vehicles and other general management, the system is built to allow handicapped parking spaces that meet the intent of the original purpose being used as expected to contribute significantly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.316-319
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• 2008

Most of campus vehicle management systems, so far, have simple functions such as managing vehicle in/out or issuing parking tickets. Recently some of them use RFID tags to count total numbers of cars in the campus, excluding exact parking position management. In this paper we propose a new campus vehicle management system using wireless sensor network location management scheme. This system adopts RSSI based location management method with some performance improvement technique. According to the experimental result, this proposed scheme can be used to implement an effective campus vehicle management system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.999-1004
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• 2010

Most of campus vehicle management systems, so far, simply manages coming in or go out of vehicles, issuing a parking tickets. Recently some of them use RFID tags to count total numbers of cars in the campus, excluding exact parking position management. In this paper we propose a new campus vehicle management system using wireless sensor network location management scheme. This system adopts RSSI based location management method with some performance improvement technique. According to the experimental result, this proposed scheme can be used to implement an effective campus vehicle management system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.110-126
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• 2024

Several studies have focused on developing the safest and most efficient path from the current location to the available parking area for vehicles entering a parking lot. In the present study, the parking lot structure and parking environment such as the lane width, width, and length of the parking space, were vaired by referring to the actual parking lot with vertical and horizontal parking. An automatic parking path planning model was proposed by collecting path data by various setting angles and environments such as a starting point and an arrival point, by putting the collected data into a deep learning model. The existing algorithm(Hybrid A-star, Reeds-Shepp Curve) and the deep learning model generate similar paths without colliding with obstacles. The distance and the consumption time were reduced by 0.59% and 0.61%, respectively, resulting in more efficient paths. The switching point could be decreased from 1.3 to 1.2 to reduce driver fatigue by maximizing straight and backward movement. Finally, the path generation time is reduced by 42.76%, enabling efficient and rapid path generation, which can be used to create a path plan for autonomous parking during autonomous driving in the future, and it is expected to be used to create a path for parking robots that move according to vehicle construction.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.305-311
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• 2021

One of the highly reliable object tracking methods is to trace objects by associating objects detected by deep learning. The detected object is represented by a rectangular box. The box has information such as location and size. Since the tracker has motion information of the object in addition to the location and size, knowing additional information about the motion of the detected box can increase the reliability of object tracking. In this paper, we present a new method of reliably estimating the moving direction of the detected object in underground parking lot. First, the frame difference image is binarized for detecting motion energy, change due to the object motion. Then, a cumulative binary image is generated that shows how the motion energy changes over time. Next, the moving direction of the detected box is estimated from the accumulated image. We use a new cost function to accurately estimate the direction of movement of the detected box. The proposed method proves its performance through comparative experiments of the existing methods.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.77-93
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• 1998

It is discussed how to locate idle vehicles of AGVS on unidirectional guide paths. The problem is modeled as a median location problem on a cyclic network. The characteristics of the optimal location are analyzed and some useful properties are suggested to reduce the solution space. Based on the properties found, several special types of networks - a pure single-loop type, the loop type with a single branching intersection and the loop type with local branching node - are also analyzed as well as the general cyclic network. In each case of the networks, a solution procedure is suggested. Some numerical examples are provided to illustrate the algorithms developed.

• Land and Housing Review
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• v.2 no.3
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• pp.217-226
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• 2011

The Seoul Metropolitan Government is striving to minimize the amount of traffic according to the supply of apartment houses along with the solution of housing shortage for the low income people through high density development near the subway area. Therefore, a stronger policy is necessary to control the traffic of the passenger cars in a subway area for the successful high density development focusing on public transportation, and especially, the estimation of the demand of cars with high reliability is necessary to control the demand of parking such as the limited supply of parking lot. Accordingly, this study developed car ownership forecasting model using Look-up Table among category analyses which are easy to be applied and have high reliability. The estimation method using Look-up-Table is possible to be applied to both measurable and immeasurable types, easy to accumulate data, and features the flexible responding depending on the changes of conditions. This study established Look-up-Table model through the survey of geographical location, the scale of housing, the accessible distance to a subway station and to a bus station, the number of bus routes, and the number of car owned with data regarding 242 blocks in Seoul City as subjects.

• Corrosion Science and Technology
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• v.20 no.2
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• pp.94-104
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• 2021

Atmospheric corrosion severity associated with aircraft parking environment was studied using metallic specimens, and temperature and humidity sensors installed at each aircraft operating base. Data were analyzed after a year of exposure. Silver was used to measure chloride deposition by integrating X-ray photoelectron spectroscopy depth profiles. Carbon steel was utilized to determine the corrosion rate by measuring the weight loss. The time of wetness was determined using temperature and humidity sensor data. Analysis of variance followed by Tukey's "honestly significant difference" test indicated that atmospheric environment inside the shelter varied significantly from that of unsheltered parking environment. The corrosion rate of unsheltered area also varies with the roof. Hierarchical clustering analysis of the measured data was used to classify air bases into groups with similar atmospheric corrosion. Bases where aircraft park at a shelter can be grouped together regardless of geographical location. Unsheltered bases located inland can also be grouped together with sheltered bases as long as the aircraft are parked under the roof. Environmental severity index was estimated using collected data and validated using the measured corrosion rate.