• Journal of the korean society of oceanography
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• v.31 no.2
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• pp.55-63
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• 1996

Distribution of suspended particulate matter, dissolved oxygen and major inorganic nutrients along a meridional section ($126^{\circ}$ 33' E) in the Cheju Strait is described along with the hydrographic and current data obtained during April 25-27, 1995. The current measurements was conducted using a vessel-mounted Acoustic Doppler Current Profiler (ADCP). Repeated coverage along an ADCP transect during 25 hours allows to calculate the daily mean along- and cross-strait currents. Measured material concentrations and the mean current speed were used to estimate the flux density (cencentration times current speed) of materials. Two types of depth distibution of flux densities were observed. for nitrate and suspended particulate matter, the depth distribution pattern of materials determines those of flux densities. However, flow patterns determine those of flux densities for dissolved oxygen, phosphate and silicic acid. The total along-strait water volume transport is about 0.3 Sv (1Sv $10^{6}$ $m^{3}/s^{-1}$). The total along-strait material transports are estimated to be 3.1 $${\times} $10^{5}$ $g/s^{-1},$ 2.4 ${\times}$ $10^{6}\;g/s^{-1},$ 7.I ${\times}$ $10^{2}\;mol/s^{-1},$ 3.I ${\times}$ $10\;mol/s^{-1},$ 1.7 ${\times}$ $10^{3}\;mol/s^{-1}$ for suspended particulate matter, dissolved oxygen, nitrate ion, silicic acid and phosphate ion, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.26-36
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• 2020

The use of existing macroscopic research of pedestrian behavior on the walking link as data is limited in determining an individual pedestrian's moving route and the level of service. In macroscopic studies, it is difficult to make quantitative indices, such as pedestrian flow rate, occupied space, density, and speed for determining the level of service on pedestrian roads. Therefore, the microscopic pedestrian route is required to establish appropriate pedestrian policies. In this study, the Yeok-Sam subway station network was examined using a micro-simulation VISSIM, which was then calibrated and validated statistically. The Pedestrian Road's Level of Service of Yeok-Sam subway station area was evaluated using the pedestrian speed as the evaluating index on the Korean highway capacity handbook.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.146-159
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• 2021

vehicle simulator as part of an empirical analysis the driving characteristics of elderly drivers. To this end, the driving characteristics of the elderly driver from previous study review. he driving characteristics of the elderly the driving elderly driver and general driverIn summarizing these experimental results, the -test showed different driving characteristics from general drivers in all items except for one side of the lane, such as driving speed and driving operation (brake, throttle, steering operation) at a significance level of 95%. Second, when changing lanes, it was difficult for elderly driver to maintain speed and secure an appropriate distance between carslderly driver changed lanes even in inappropriate situations (short distances between cars). Third, in unexpected situation, elderly drivers needed more distance and time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.50-61
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• 2022

Snow, rain, fog, and particulate matter interfere with the vehicle driver's vision, which causes a non-secure safety distance and an increase in speed deviation, causing repetitive large-scale traffic accidents. This study developed a road environment sensor capable of measuring 11 types of fog, snow, rain, temperature, humidity, direction of wind, speed of wind, Insolation, atmospheric pressure, fine particles, rainfall, etc. and compared the visibility measured by the infrared signal value of the development sensor. The relationship between the existing fog visibility sensor and the development sensor measurement was derived from data measured at a visibility of 500m or less that directly affects road safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.83-95
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• 2022

This paper proposes a system that performs object detection and distance estimation for application to autonomous vehicles. Object detection is performed by a network that adjusts the split grid to the input image ratio using the characteristics of the recently actively used deep learning model YOLOv4, and is trained to a custom dataset. The distance to the detected object is estimated using a bounding box and homography. As a result of the experiment, the proposed method improved in overall detection performance and processing speed close to real-time. Compared to the existing YOLOv4, the total mAP of the proposed method increased by 4.03%. The accuracy of object recognition such as pedestrians, vehicles, construction sites, and PE drums, which frequently occur when driving to the city center, has been improved. The processing speed is approximately 55 FPS. The average of the distance estimation error was 5.25m in the X coordinate and 0.97m in the Y coordinate.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.2
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• pp.132-140
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• 2023

In this study, rotary magnet holder (RMH) was manufactured to analyze the ion transport effect according to the rotating magnetic field for the hydrogen production efficiency by alkaline water electrolyte. In the experiment, the voltage signal according to the magnet arrangement inside the RMH, the rotation speed, and the rotation time was measured using the voltage measurement module. As a result of the voltage signal measurement experiment, the average potential difference increased as the rotation speed of the RMH increased. Through the results of the voltage signal measurement experiment, the most efficient magnet arrangement (case 2) was applied to the RMH to conduct a water electrolysis experiment. A 20% NaOH aqueous solution was filled in the electrolytic cell, and a direct current 2 V constant voltage was applied to measure the current value according to the RMH rotation to compare the hydrogen generation amount. When rotating at 100 RPM, the hydrogen production efficiency increased by 8.06% compared to when not rotating. Considering the area exceeding +25 mA, which was not measured at the beginning of the experiment, an increase in hydrogen production of about 10% or more can be expected.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.116-130
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• 2023

Expressways play pivotal roles in cargo transportation because of their superior accessibility and mobility compared to rail and air. On the other hand, there is a limit to the accurate calculation of cargo transportation performance using existing highways owing to the mixture of vehicle types and difficulty in identifying cargo loads of individual cargo vehicles. This paper presents an algorithm for calculating more reliable cargo transportation performance using big data. The traffic performance (veh·km/day) was derived using the data collected from Toll Collecting System. The average tolerance weight for each vehicle type and the cargo load unit (ton/unit) considering it was calculated using vehicle specification information data and high-speed and low-speed axis data. This study calculated the cargo transportation performance by section and type using various online integrated highway data and presented a method for calculating the transportation performance by linking open business offices and private highways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.95-107
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• 2016

The axle weight of a vehicle in motion can be measured with a low-speed or high-speed weigh-in-motion (WIM). However, the axial load dynamically change depending on the vehicle's characteristics-such as the chassis or axle structure-or the characteristics of the driving environment such as road flatness. The changes in dynamic load lead to differences between the vehicle's weight measured at rest and the vehicle's weight measured in motion. For this Study, an experiment was conducted with an instrumented vehicle to analyze the range of errors caused by uncontrollable environmental factors by identifying the characteristics of the dynamic load changes of a vehicle in motion, and determine the appropriate scale for the accuracy evaluation of a high-speed WIM, as a preparatory research for the introduction of unmanned overweight enforcement systems in the future. The key findings from the experiment are summarized as follows. First, The gross weight of the tested vehicle changed by approximately 1% at low velocities and approximately by 4% at high velocities, and the vehicle's axle weight changed by approximately 1-3%, at low velocities and by 2-9% at high velocities. A single axle showed larger weight changes than individual axles in a group. Secondly, The vehicle's gross weight and the axle weight on the impact section were up to eight times and three-to-twelve times higher, respectively, than its gross weight and the axle weight on the flat section. The vibration frequency of the vehicle's dynamic load was measured at between 2.4 and 5.8Hz, and found to return to the normal amplitude after moving approximately 30 meters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.44-55
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• 2013

Intelligent transportation systems allow us to have valuable opportunities for collecting reliable wide-area coverage traffic and weather data. Significant efforts have been made in many countries to apply these data. This study identifies the critical points for classifying rain intensity by analyzing the relationship between rainfall and the amount of speed reduction. Then, traffic prediction performance by rain intensity level is evaluated using relative errors. The results show that critical points are 0.4mm/5min and 0.8mm/5min for classifying rain intensity (slight, moderate, and heavy rain). The best prediction performance is observable when previous five-block speed data is used as inputs under normal weather conditions. On the other hand, previous two or three-block speed data is used as inputs under rainy weather conditions. The outcomes of this study support the development of more reliable traffic information for providing advanced traffic information service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.11-23
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• 2011

The objective of this paper is to develop a daily pattern clustering algorithm using historical traffic data that can reliably detect under various traffic flow conditions in urban streets. The developed algorithm in this paper is categorized into two major parts, that is to say a macroscopic and a microscopic points of view. First of all, a macroscopic analysis process deduces a daily peak/non-peak hour and emphasis analysis time zones based on the speed time-series. A microscopic analysis process clusters a daily pattern compared with a similarity between individuals or between individual and group. The name of the developed algorithm in microscopic analysis process is called "Two-step speed clustering (TSC) algorithm". TSC algorithm improves the accuracy of a daily pattern clustering based on the time-series speed variation data. The experiments of the algorithm have been conducted with point detector data, installed at a Ansan city, and verified through comparison with a clustering techniques using SPSS. Our efforts in this study are expected to contribute to developing pattern-based information processing, operations management of daily recurrent congestion, improvement of daily signal optimization based on TOD plans.