• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.31-39
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• 2012

This study aims to suggest a methodology of localizing and calibrating parameters, such as acceleration, deceleration, and lane changing which are the basis of car following model in interrupted traffic flow to overcome the limitation of origin and destination based transportation simulation and to verify the application of activity-based model for use in Korean roadway condition in a large scale area or a city. Especially, we figured out that a proper cell size reflecting Korean traffic conditions is 1.0m rather than 7.5m which is default size and a methodology of tracking vehicle behavior characteristics through tracking vehicle ID is suggested on this study. In addition, vehicle running characteristics in real interrupted traffic flow is analyzed through subdividing vehicle types and updating vehicle type ratio. For verification of suggested model, some portion of Dalgubyul-ro in the Daegu city is tested, and the possibility of realization of interrupted traffic flow in simulation is studied.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.153-172
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• 2018

Overloading of Commercial vehicles have been an important area of transportation as one of the main causes of pavement damage, bridge collapse, severe traffic accident, etc. In this study, we analyzed the effects of overweight prevention by analyzing overweight driving patterns and using weight sensors. First, we analyzed relevant literatures of overweight and surveyed the commercial weight sensors. Then we chose the typical type of overweight vehicles based of overweight enforcement data analysis. MEMs inclinometer weight sensor were installed to 10 test vehicles and data was collected by weight sensors and gps in real time. As a result of gross vehicle weight and axle weight analysis, it was found weight sensor could decrease overweight rate. However, since the number of samples of test vehicles is insufficient to represent the whole commercial vehicle, further studies are deemed possible through the extension test.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.142-155
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• 2019

This study was conducted with the aim of developing a system to collect taxi GPS probe information to prevent link defects and to improve the accuracy of the standard link-based travel speed by determining when to go into and come out the link. For this purpose, a framework and algorithm consisting of a five-step process for standard link-based map matching and individual vehicle travel speed are presented and used it to calculate the average travel speed of the service link. Two on-site surveys of Teheran and Hakdong-ro were conducted to verify the results by the methods proposed in this paper. On the basis of the overall time of the field survey, the deviation in the travel speed was 0.2 km/h and 0.6 km/h, the accuracy was 99% and 96%, and the MAPE(Mean Absolute Percentage Error) was 1% and 4% in Teheran and Hakdong-ro, respectively. These results were more accurate thand those obtained using conventional methodologies without standard links.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.61-73
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• 2020

Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.107-117
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• 2020

With the recent development of autonomous vehicles, various sensors installed in vehicles have become common, and big data generated from those sensors is increasingly being used in the transportation field. In this study, we proposed a grid index method to efficiently process real-time vehicle sensing big data and public data such as road weather. The applicability and effect of the proposed grid space division method and grid ID generation method were analyzed. We created virtual data based on DTG data and mapped to the road link based on coordinates. As a result of analyzing the data processing speed in grid index method, the data processing performance improved by more than 2,400 times compared to the existing link unit processing method. In addition, in order to analyze the efficiency of the proposed technology, the virtually generated data was mapped and visualized.

• 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.22-39
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• 2021

This study estimated mode choice models for access travel and neighborhood travel from an SP survey in metropolitan areas where shared e-scooter services are offered. Model results show that travel time and travel cost have negative effects on mode utility. It is also revealed that people are more sensitive to travel time in access travel, whereas they are more influenced by travel cost in neighborhood travel. Looking at individual and household attributes, it has a positive effect when under 40 yerars of age, owning bikes, being a public transportation user, while it has been shown a negative effect in less than 3 million won in monthly household income and owning individual cars.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.192-207
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• 2020

In industrial fields like big factories, efficient management of resources is critical in terms of time and expense. So, inefficient management of resources leads to additional costs. Nevertheless, in many cases, there is no proper system to manage resources. This study proposes a system to manage and track large-scale resources efficiently. We attached Bluetooth 5.0-based beacons to our target resources to track them in real time, and by saving their transportation data we can understand flows of resources. Also, we applied a diagonal survey method to estimate the location of beacons so we are able to build an efficient and accurate system. As a result, We achieve 47% more accurate results than traditional trilateration method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.46-56
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• 2021

Predicting the incident clearance time is important for eliminating the high transportation costs and congestion from non-repetitive congestion caused by incidents. In this study, the factors influencing the clearance time suitable for domestic road conditions were analyzed, using a training dataset for predicting the incident clearance time using artificial neural networks. In a previous study, the under-prediction problem for high incident clearance time was used. In the present study, over-sampling training data applied using the SMOGN technique was obtained and applied to the model as a solution. As a result, the DNN model applying the SMOGN technique could compensate for the limitations of the previously developed prediction model by predicting the clearance time with the highest accuracy among the models developed in the research process with MAE = 18.3 minutes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.30-38
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• 2022

As of 2020, 1,564 roundabouts have been installed and operated to prevent major traffic accidents and promote safe and smooth passage over the past 10 years. According to the Korea Transportation Research Institute, the number of accidents decreased by an average of 43.8% per year, fatal accidents by 50%, and serious injuries by 48.1%, confirming the safety effect. However, most intersections with high pedestrian traffic, such as children's protection areas near elementary schools, operate signal intersections. Therefore, in this study, a simulation was performed through the VISSM program to conduct a study on the pedestrian-centered roundabout installation method. This study was conducted to ensure that pedestrians can have the right of way safely by installing and operating traffic lights at crosswalks on roundabouts located in urban areas or child protection zones.