• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.182-191
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• 2015

The Korean government introduced an automated speed enforcement system (ASES), which uses traffic enforcement cameras, to counteract safety issues that are caused by speeding. As the information of the traffic enforcement camera locations is provided to the drivers via navigation systems and mobile applications in a timely manner, drivers can avoid enforcement by momentarily diminishing their speeds only near the camera locations. To prevent drivers' evasional behavior and improve the effectiveness of ASES, section control, which enforces speeding vehicles by measuring their average travel speeds over a stretch of road and checking against the speed limit, has been recently implemented. In this study, Section Speed Enforcement Zone and Comparison Zone are compared in terms of traffic stream characteristics under free flow conditions. To this end, loop detector data were obtained from the three study sites and analyzed. The study results demonstrated that drivers maintain their speeds below the speed limit over the enforcement section with a lower variance of speeds.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.1
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• pp.72-85
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• 2012

Today, although most bluetooth hands-free devices within a vehicle provide telephone service functions such as voice communication, caller id display and SMS message display and so on, they do not provide a function that displays Internet-based text data. We need to develop a scheme that displays the internet-based text data including existing hands-free function because the request for using the Internet service is increasing within a vehicle recently. The proposed bluetooth device application includes advanced function such as SNS message arrival notification, the message display function and we chose Android as the implementation mobile platform giving consideration to the fact that most SNS applications operate on Android and the platform is easily embedded into small embedded device. Smartphone or tablet PC connected with the proposed bluetooth device is an Android-based device and we designed a form of Android app for the function implementation of the devices. When the audio-text gateway app receives SNS text data, it extracts title and sender information from the message header information in a form of text data and sends them via ACL (Asynchronous Connection-Oriented) link to the bluetooth device showing the data on the screen. Android-based bluetooth devices are not possible to play voice through speaker because the bluetooth hands-free or headset profile ported within Android platform normally only includes audio gateway's function. The proposed bluetooth device application, therefore, applies the streaming scheme that sends data via ACL link instead of the way that sending them via SCO (Synchronous Connection-Oriented) link.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.70-81
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• 2020

Point-by-point data, which is abundantly collected by vehicles with embedded GPS (Global Positioning System), generate useful information. These data facilitate decisions by transportation jurisdictions, and private vendors can monitor and investigate micro-scale driver behavior, traffic flow, and roadway movements. The information is applied to develop app-based route guidance and business models. Of these, speed data play a vital role in developing key parameters and applying agent-based information and services. Nevertheless, link speed values require different levels of physical storage and fidelity, depending on both collecting and reporting intervals. Given these circumstances, this study aimed to establish an appropriate collection interval to efficiently utilize Space Mean Speed information by vehicles with embedded GPS. We conducted a comparison of Probe-vehicle data and Image-based vehicle data to understand PE(Percentage Error). According to the study results, the PE of the Probe-vehicle data showed a 95% confidence level within an 8-second interval, which was chosen as the appropriate collection interval for Probe-vehicle data. It is our hope that the developed guidelines facilitate C-ITS, and autonomous driving service providers will use more reliable Space Mean Speed data to develop better related C-ITS and autonomous driving services.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.80-85
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• 2011

This paper presents the design of the power-assisted controller for the in-wheel type smart wheelchair by using torque estimation that is predicted by relationship between input voltage and output wheel angular velocity. Nowadays, interest of the moving assistant aids is increased according to the increase in population of the elderly and the handicapped person. However some of the moving assistant aids have problems. For example, manual wheelchair has difficulty moving at the slope, because users lack the muscular strength of their arm. In electric wheelchair case, users should be weak by being decreased muscles of upper body. To overcome these problems, power-assisted electric wheelchair are proposed. Most of the power-assisted electric wheelchair have the special rims that can measure the user's power. In here, the rims have to be designed to install the sensors to measure user's power. In this paper, we don't design the rim to measure the man power. To predict the man power, we propose a control algorithm of the in-wheeled electric wheelchair by using torque estimation from the wheel. First, we measure the wheel velocity and voltage at the in-wheel electric wheelchair. And then we extract driving will forces by using proposed mathematical model. Also they are applied at the controller as the control input, we verify to be able to control in-wheel type smart wheelchair by using simulation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.219-231
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• 2019

The specifications of signboards are set for each type of signboards, but the shape and size of the signboard actually installed are not uniform. In addition, because the colors of the signboard are not defined, so various colors are applied to the signboard. Methods for recognizing signboards can be thought of as similar methods of recognizing road signs and license plates, but due to the nature of the signboards, there are limitations in that the signboards can not be recognized in a way similar to road signs and license plates. In this study, we proposed a methodology for recognizing plate-type signboards, which are the main targets of illegal and old signboards, and automatically extracting areas of signboards, using the deep learning-based Faster R-CNN algorithm. The process of recognizing flat type signboards through signboard images captured by using smartphone cameras is divided into two sequences. First, the type of signboard was recognized using deep learning to recognize flat type signboards in various types of signboard images, and the result showed an accuracy of about 71%. Next, when the boundary recognition algorithm for the signboards was applied to recognize the boundary area of the flat type signboard, the boundary of flat type signboard was recognized with an accuracy of 85%.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.419-432
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• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.207-213
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• 2019

The fuel-cut coast-down driving mode is activated when the acceleration pedal is released with transmission gear engaged, and it's a default function for electronic-controlled engine of vehicles. The fuel economy becomes better because fuel injection stops during fuel-cut driving mode. A fuel-cut detection method is suggested in the study and it's based on the speed, acceleration and road gradient data from GPS sensor. It detects fuel-cut driving mode by comparing calculated acceleration and realtime acceleration value. The one is estimated with driving resistance in the condition of fuel-cut driving and the other is from GPS sensor. The detection accuracy is about 80% when the method is verified with road driving data. The result is estimated with 9,600 data set of vehicle speed, acceleration, fuel consumption and road gradient from test driving on the road of 12km during 16 minutes, and the road slope is rather high. It's easy to detect fuel-cut without injector signal obtained by connecting wire. The detection error is from the fact that the variation range of speed, acceleration and road gradient data, used for road resistance force, is larger than the value of fuel consumption data.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.7
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• pp.205-214
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• 2021

For smart manufacturing, most semiconductor sites utilize automated material handling systems(AMHS). As one of the AMHSs, the OHT control system(OCS) manages overhead hoist transports(OHT) that move along rails installed on the ceiling. This paper proposes a real-time scheduling system to efficiently allocate and control the OHTs in semiconductor logistics processes. The proposed system, as an independent subsystem within the OCS, is interconnected with the main subsystem of the OCS, so that it can be easily modified without the effect of other systems. To develop the system, we first identify the functional requirements of the semiconductor logistics process and classify several types of control scenarios of the OHTs. Next, based on SEMI(Semiconductor Equipment and Materials International) standard, we design sequence diagrams and interface messages between the subsystems. The developed system is interoperated with the OCS main subsystem and the database in real time and performs two major roles: 1) OHT dispatching and 2) pathfinding. Six integrated tests were carried out to verify the functions of the developed system. The system was normally operated on six basic scenarios and two exception scenarios and we proved that it is suitable for the mission planning of the OHTs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.417-425
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• 2022

Interest in micro cars is growing around the world, and policy support for micro cars has been increasing in Korea. It is important to meet minimum safety standards for the operation of micro cars on roads due to concerns around micro car safety and the limited driving range of micro cars. In this study, visibility experiments that included safety identification of micro cars were conducted to try and prevent a decrease in driver reaction time. Safety identification lights were installed to the rear of a micro car, and the visibility and discomfort of the vehicle were evaluated to determine whether the micro car was safe to drive on an expressway. As a result, the installation effect of Micro car which install safety identification lamp was found when joining the point at an acceleration lane of the grade separation intersection, and that light on/off could be effective when entering an expressway. If the micro car operation plan proposed in this study is applied, the safety of micro cars on expressways can be increased by improving the visibility of micro car.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.569-575
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• 2010

The occupancy based O/D is essential for measuring efficiency of various transportation policies like HOV/HOT lane, ramp metering, and public parking station. There has been many studies on occupancy survey methodology and O/D estimation using TCS (Toll Collection System) data separately. The occupancy O/D estimation methodology using TCS data has not been attempted thus far. An overall process from data collection stage to the occupancy O/D estimation stage has been suggested. Field survey was performed at the northbound Seoul toll station of Gyeongbu Expressway by each 2 hours of AM peak, PM non-peak, PM peak, midnight periods on a day. The process of matching the TCS data and field survey data classified by tollbooth ID, car type/mode, and arrival time was also performed. One typical output of the results showed that the ratio of single occupancy vehicles bounding for Seoul during the AM peak amounted to 60%. With the key output of this study and the specific O/D estimation methodology suggested, the whole centroid-to-centroid occupancy O/D of the country could be available, and then various applications in which the occupancy information is required could be possible.