• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.25-43
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• 2005

In modern automated container terminals, automated guided vehicle (AGV) systems are considered a viable option for the horizontal tansportation of containers between the stacking yard and the quayside cranes. AGVs in a container terminal move rather freely and do not follow fixed guide paths. For an efficient operation of such AGVs, however, a sophisticated traffic management system is required. Although the flexible routing scheme allows us to find the shortest possible routes for each of the AGVs, it may incur many coincidental encounters and path intersections of the AGVs, leading to collisions or deadlocks. However, the computational cost of perfect prediction and avoidance of deadlocks is prohibitively expensive for a real time application. In this paper, we propose a traffic control method that predicts and avoids some simple, but at the same time the most frequently occurring, cases of deadlocks between two AGVs. More complicated deadlock situations are not predicted ahead of time but detected and resolved after they occur. Our method is computationally cheap and readily applicable to real time applications. The efficiency and effectiveness of our proposed methods have been validated by simulation.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.6
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• pp.749-762
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• 2019

In recent years, in urban areas, underground of roads are being promoted in order to resolve traffic congestion and to secure green spaces, and due to the low ratio of large vehicles, they are planned or constructed as road tunnels for small cars only. In addition, the tunnels being built in the city is a tendency to be enlarged to play the role of main roads. Accordingly, the capacity of the ventilation system is increasing and various ventilation methods are required, and the importance of maintenance after the completion of the tunnel such as the operating cost of the ventilation system is emphasized. Therefore, the need for optimization of the operation stage for reducing the power consumption of the ventilation system and the study of the ventilation system operation control logic is increasing. In this study, the study on the necessity of the optimization of operation stage and control logic of the ventilation system was carried out to realize the energy-saving operation for the small car only passing through tunnels which is applied of ① jet fan and combination ventilation system (② jet fan + air purifying equipment, ③ jet fan + vertical shaft, ④ jet fan + supply air semi-transverse). As a result of this study, there can be various operating combinations in the case of the combined ventilation system, and even though the amount of ventilation air is the same, the operating power varies greatly according to the operating combinations. It was found that operating the axial fan first rather than the jet fan first operation method has an effect on power saving.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1369-1382
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• 2005

Vehicle segmentation, which extracts vehicle areas from road scenes, is one of the fundamental opera tions in lots of application areas including Intelligent Transportation Systems, and so on. We present a vehicle segmentation approach for still images captured from outdoor CCD cameras mounted on the supporting poles. We first divided the input image into a set of two-dimensional grids and then calculate the feature values of the edges for each grid. Through analyzing the feature values statistically, we can find the optimal rectangular grid area of the vehicle. Our preprocessing process calculates the statistics values for the feature values from background images captured under various circumstances. For a car image, we compare its feature values to the statistics values of the background images to finally decide whether the grid belongs to the vehicle area or not. We use dynamic programming technique to find the optimal rectangular gird area from these candidate grids. Based on the statistics analysis and global search techniques, our method is more systematic compared to the previous methods which usually rely on a kind of heuristics. Additionally, the statistics analysis achieves high reliability against noises and errors due to brightness changes, camera tremors, etc. Our prototype implementation performs the vehicle segmentation in average 0.150 second for each of $1280\times960$ car images. It shows $97.03\%$ of strictly successful cases from 270 images with various kinds of noises.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.71-77
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• 2010

It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.34-41
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• 2017

Vehicle to Infrastructure(V2I) communication means the technology between the vehicle and the roadside unit to provide the Intelligent Transportation Systems(ITS) and Telematic services. The vehicle collects information about the probe data through the evolved Node B(eNodeB) and after that eNodeB provides road conditions or traffic information to the vehicle. To provide these V2I communication services, we need a link adaptation technology that enables reliable and higher transmission rate. The receiver transmits the estimated Channel State Information(CSI) to transmitter, which uses this information to enable the link adaptation. However, due to the rapid channel variation caused by vehicle speed and the processing delay between the layers, the estimated CSI quickly becomes outdated. For this reason, channel interpolation and prediction scheme are needed to achieve link adaptation in V2I communication system. We propose the Advanced Discrete Prolate Spheroidal Sequence(ADPSS) channel interpolation and prediction scheme. The proposed scheme creates an orthonomal basis, and uses a correlation matrix to interpolate and predict channel. Also, smoothing is applied to frequency domain for noise removal. Simulation results show that the proposed scheme outperforms conventional schemes with the high speed and low speed vehicle in the freeway and urban environment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.32-39
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• 2006

5.8GHz DSRC(Dedicated Short Range Communications) is a short to medium range communications service that supports both public safety and private operations in roadside to vehicle and vehicle communication. However the 5.8GHz frequency may cause the shadowing effect or communication blocking problem when there is an obstacle or another vehicle between RSE (Road Side Equipment) and OBE (On Board Equipment). In this paper, to solve this problem of the 5.8GHz DSRC, we propose a relay protocol based on the standard of DSRC radio communication between RSE and OBE in the 5.8GHz band made by TTA (Telecommunication Technology Association). By using the proposed relay protocol to DSRC system and intervehicle communication, we also consider a fixed relay protocol and mobile relay protocol. We expect to apply this relay protocol for the DSRC intervehicle communication and video communication between drivers and safe distance among vehicles in the near future.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.5
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• pp.531-538
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• 2016

Driving behaviors such as speeding and illegal u-turn which violate traffic rules are main causes of car accidents, and they can lead to serious accidents. Bus drivers are less aware of dangers of illegal u-turn, and infrastructures such as traffic enforcement equipment and watchmen are deficient. This research aims to develop technology for estimating driving behaviors based on map-matching in order to prevent illegal u-turns. For this research, 23,782 of u-turn permit data and 146,000 of speed limit data are collected nationwide, and an estimation algorithm is built with these data. Then, an application based on android is developed, and finally, tests are conducted to assess the accuracy in data computations and GPS data map-matching, and to extrapolate driving behavior. As a result of the tests, the accuracy results in the map-matching is 86% and the assessment of driving behavior is 83%, while the display of the data output yielded 100% accuracy. Additional research should focus on improvement in accuracy through the development of a robust monitoring system, and study of service scenarios for technology application.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.1-7
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• 2009

The final goal of ITS and ETC will be to improve the traffic efficiency and mobile safety without new road construction. DSRC system is emerging nowadays as a solution of them. China DSRC standard which was released in May 2007 has low bit rate, short message and simple MAC control. The DSRC system users want a long lifetime over 1 year with just one battery. In this paper, we propose the SoC of very low power consumption architecture. Several digital logic concept and analog power control logics were used for very low power consumption. The SoC operation mode and clock speed, operation voltage range, wakeup signal detector, analog comparator and Internal Voltage Regulator & External Power Switch were designed. We confirmed that the SoC power consumption is under 8.5mA@20Mhz, 0.9mA@1Mhz in active mode, and under 5uA in power down mode, by computer simulation. The design of SoC was finished on Aug. 2008, and fabricated on Nov. 2008 with $0.18{\mu}m$ CMOS process.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.10-21
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• 2008

The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6604-6610
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• 2015

In this paper, an efficient Wireless Access in Vehicular Environment (WAVE) packet transmission scheme for railroad communication is proposed. WAVE communication is a wireless local area network (WLAN) based communication and it is developed to be suitable for vehicular communication. There has been a lot of study on WAVE's applicability to Intelligent Transport System (ITS). As one of main transportation methods, by using WAVE, quality of railroad communication including WLAN based Communication Based Train Control (CBTC) can be enhanced and variety of railroad communication systems can be integrated into WAVE. However, there are technical challenges to adopt WAVE in railroad communications. For the simplest single-PHY WAVE, time division alternation of 50ms between Control Channel (CCH) and Service Channel (SCH) is required. Since there are delay sensitive railroad traffic types, alternation operation of CCH and SCH may cause performance degradation. In this paper, after identifying a couple of problems based on detailed analysis, a novel packet transmission scheme under railroad environment is proposed. In order to verify if the proposed scheme meets the requirement of railroad communication, WAVE transmission is mathematically modeled.