• 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.22 no.6
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• pp.141-156
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• 2023

This study aims to improve understanding of freight movement, crucial for logistics facility investment and policy making. It addresses the limitations of traditional freight truck traffic data, aggregated only at city and county levels, by developing a new methodology. This method uses trip chain data for more detailed, facility-level analysis of freight truck movements. It employs DTG (Digital Tachograph) data to identify individual truck visit locations and creates H3 system-based polygons to represent these visits spatially. The study also involves an algorithm to dynamically determine the optimal spatial resolution of these polygons. Tested nationally, the approach resulted in polygons with 81.26% spatial fit and 14.8% error rate, offering insights into freight characteristics and enabling clustering based on traffic chain characteristics of freight trucks and visited facility types.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.10-23
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• 2016

With requiring circumspections using big data, this study attempts to develop and apply the search method for audit issues relating to the ITS policy or program. For the foregoing, the auditing process of the board of audit and inspection was converged with the theoretical frame of boundary analysis proposed by William Dunn as an analysis tool for audit issues. Moreover, we apply the text mining technique in order to computerize the analysis tool, which is similar to the boundary analysis in the concept of approaching meta-problems. For the text mining analysis, specific model we applied the antisymmetry-symmetry compound lexeme-based LDA model based on the Latent Dirichlet Allocation(LDA) methodologies proposed by David Blei. The several prime issues were founded through a case analysis as follows: lack of collection of traffic information by the urban traffic information system, which is operated by the National Police Agency, the overlapping problems between the Ministry of Land, Infrastructure and Transport and the Advanced Traffic Management System and fabrication of the mileage on digital tachograph.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.152-166
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• 2022

This study analyzed the causal relationship among operating characteristics of commercial freight vehicles, dangerous driving behaviors, and traffic accident risk. The study applied the existing accident cause and prevention theory to arrive at this relationship. Data related to working characteristics of driver, driving experience, driving ability, driving psychology, vehicle characteristics (size), dangerous driving behavior, and traffic accidents were collected from 303 commercial freight vehicle drivers. Working characteristics and dangerous driving behavior data are based on the driver's digital driving record. The traffic accident data is based on the insurance accident data reflecting actual traffic accidents. First, a structural equation model was built and verified using the model fitness index. Then, the developed model was used to analyze the causal relationship between multiple independent and dependent variables simultaneously. Four dangerous driving behaviors (sudden deceleration, sudden acceleration, sudden passing, and sudden stop) were found to be highly related to traffic accidents. The results further indicate that it is necessary to establish a safety management policy and intensive management for small-sized freight vehicles, drivers with insufficient driving ability, and drivers with dangerous driving behaviors. Such policy and management are expected to reduce traffic accidents effectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.209-220
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• 2022

With the worldwide spread of African swine fever, interest in livestock epidemics has increased. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but there are no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted the trajectory of livestock-related vehicles using the facility-visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority. The results are presented as exposure indices aggregating the link-time occupancy of each vehicle. As a result, 274,519 livestock-related vehicle trajectories were extracted, and the exposure values by link and zone were derived quantitatively. This study highlights the need for prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.34-48
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• 2019

The purpose of this study was two-fold; first, to develop safety performance functions (SPF) using transportation-related big data for all types of roads in Korea were developed, Second, to provide basic information to develop measures for relatively dangerous roads by evaluating the safety grade for various roads based on it. The coordinates of traffic accident data are used to match roads across the country based on the national standard node and link system. As independent variables, this study effort uses link length, the number of traffic volume data from ViewT established by the Korea Transport Research Institute, and the number of dangerous driving behaviors based on the digital tachograph system installed on commercial vehicles. Based on the methodology and result of analysis used in this study, it is expected that the transportation safety improvement projects can be properly selected, and the effects can be clearly monitored and quantified.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.30-42
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• 2021

The amount of compensation and the number of cases owing to car damage from pot holes on highways across the country increased by about 4.2 times and 3.5 times, respectively, in 2019 compared to 2015. Due to the increase in damage caused by these road hazards, the Ministry of Land, Infrastructure and Transport is developing technologies and services that can collect road hazard information by using devices on commercial vehicles (DTGs, black boxes, ADASs). In preparation for the development of these technologies, this study conducted an integrated assessment of algorithms developed for interrupted-flow and uninterrupted-flow traffic under three scenarios in order to provide road hazard information to drivers and road managers. As a result, the overall accuracy of the integrated assessment was derived at 81.88%. Errors generated in this integrated assessment reflect only missing data in less than 1 minute, GPS coordinate location and algorithm related errors, taking into account the purpose and assumptions of the assessment. Among them, we derive an accuracy of 90.15%overall by calibrating GPS error data. The results of this study can be used as basic data for improving the accuracy of location-based information collected by commercial vehicles and for policy development.