• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.1-11
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• 2019

The accident of mass transit such as a bus could draw the large casualties and this induces social and economic losses. Recently, severe bus accidents caused by tiredness and inattention of bus drivers occurred and those lead to growing interest in bus accidents and the drivers' work environment. Therefore, this study analyzes the accident based on the work environment of bus drivers and route-bus categories. For the research, this study collected digital tachograph data and the bus company information for 271 domestic bus companies in 2017 and used ANOVA test and chi-square test as statistical methodologies. As a result, we figured out there are statistically significant differences in the accident according to the working environments. Especially, the present study confirmed the intracity bus with working every other day has the most frequent accidents. We expect that the results of this study be used as foundations for the improvement of working conditions to reduce route-bus accidents in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.96-110
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• 2018

As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.43-55
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• 2019

Smart phone based navigation applications are very useful in everyday life. Cost-effective and user friendly navigation can be provided to the user by many applications available in market. Using the Smart phone these navigation applications provide accurate navigation for outdoor locations. But providing an accurate navigation underground space such as subway station is still a challenge. It is hence more convenient and appropriate for mobility services if the visitors could simply view the guidance of the subway station on their mobile phone, wherever and whenever it is needed. This study develops a algorithm for indoor navigation with the help of Augmented Reality(AR) and QR marker code from the entrance to the train platform for users. This indoor navigation uses AR and QR maker codes for two purposes: to provide the user link to the subway station location and to provide the current guidance details to the user. This Smart phone algorithm that uses a smart phone optical tool to decode the QR marker to determine the location information and provide guidance to the AR without indoor Maps. This algorithm also provides a module to guide mobility vulnerable to the Barrier Free route to destination.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.1-13
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• 2018

The number of deaths in Korea is higher than the OECD average. Therefore, an e-Call system is being developed as a vehicle ICT-based emergency rescue system that automatically detects an accident in the event of a vehicle accident and transmits related information to the center. In order to overcome the limitations of social acceptability and function of e-Call system, we propose a model that allows users to be aware of the necessity of service voluntarily. We predicted the market share of e-call services according to the proposed business model and analyzed it through B/C analysis. Benefits are calculated on a penetration basis, and device purchase and communications costs are calculated for each period. B/C analysis shows that pessimistic scenarios are 0.98 in 2025 and 1.01 in 2030. In an optimistic scenario, it is 1.05 in 2025 and 1.20 in 2030, which is more economical.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.126-141
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• 2019

One of the Cooperative Intelligent Transportation System(C-ITS) priority services is collision prevention support service. Several studies have considered V2I2V communication-based collision prevention support services using Artificial Neural Networks(ANN). However, such services still show some issues due to a low penetration of C-ITS devices and large delay, particularly when loading massive traffic data into the server in the C-ITS center. This study proposes the Artificial Neural Network-based Collision Warning Service(ACWS), which allows upstream vehicle to update pre-determined weights involved in the ANN by using real-time sectional traffic information. This research evaluates the proposed service with respect to various penetration rates and delays. The evaluation result shows the performance of the ACWS increases as the penetration rate of the C-ITS devices in the vehicles increases or the delay decreases. Furthermore, it reveals a better performance is observed in more advanced ANN model-based ACWS for any given set of conditions.

• Journal of Life Science
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• v.29 no.2
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• pp.181-190
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• 2019

The purpose of this study was to acquire the active compounds of Anisi stellati fructus (ASF) and to analyze the genes and diseases it targets, focusing on its antibacterial effects using a system pharmacological analysis approach. Active compounds of ASF were obtained through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database and Analysis Platform. This contains the pharmacokinetic properties of active compounds and related drug-target-disease networks, which is a breakthrough in silico approach possible at the network level. Gene information of targets was gathered from the UnitProt Database, and gene ontology analysis was performed using the David 6.8 Gene Functional Classification Tool. A total of 201 target genes were collected, which corresponded to the nine screened active compounds, and 47 genes were found to act on biological processes related to antimicrobial activity. The representative active compounds involved in antibacterial action were luteolin, kaempferol, and quercetin. Among their targets, Chemokine ligand2, Interleukin-10, Interleukin-6, and Tumor Necrosis Factor were associated with more than three antimicrobial biological processes. This study has provided accurate evidence while saving time and effort to select future laboratory research materials. The data obtained has provided important data for infection prevention and treatment strategies.

• Safety and Health at Work
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• v.13 no.3
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• pp.263-268
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• 2022

Health care workers (HCWs) are more than ten times more likely to be infected with coronavirus infectious disease 2019 (COVID-19) than the general population, thus demonstrating the burden of COVID-19 among HCWs. Factors that expose HCWs to a differentially high-risk of COVID-19 acquisition are important to elucidate, enable appropriate public health interventions to mitigate against high risk and reduce adverse outcomes from the infection. We conducted a systematic review and meta-analysis to summarize and critically analyze the existing evidence on SARS-CoV-2 risk factors among HCWs. With no geographical limitation, we included studies, in any country, that reported (i) the PCR laboratory diagnosis of COVID-19 as an independent variable (ii) one or more COVID-19 risk factors among HCWs with risk estimates (relative risk, odds ratio, or hazard ratio) (iii) original, quantitative study design, and published in English or Mandarian. Our initial search resulted in 470 articles overall, however, only 10 studies met the inclusion criteria for this review. Out of the 10 studies included in the review, inadequate/lack of protective personal equipment, performing tracheal intubation, and gender were the most common risk factors of COVID-19. Based on the random effects adjusted pooled relative risk, HCWs who reported the use of protective personal equipment were 29% (95% CI: 16% to 41%) less likely to test positive for COVID-19. The study also revealed that HCWs who performed tracheal intubations were 34% (95% CI: 14% to 57%) more likely to test positive for COVID-19. Interestingly, this study showed that female HCWs are at 11% higher risk (RR 1.11 95% CI 1.01-1.21) of COVID-19 than their male counterparts. This article presents initial findings from a living systematic review and meta-analysis, therefore, did not yield many studies; however, it revealed a significant insight into better understanding COVID-19 risk factors among HCWs; insights important for devising preventive strategies that protect them from this infection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.57-66
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• 2022

The Road Management Administration is cracking down on overloaded vehicles by installing low-speed or high-speed WIMs at toll gates and main lines on expressways. However, in recent years, the act of intelligently evading the overloaded-vehicle control system of the Road Management Administration by illegally manipulating the variable axle of an overloaded truck is increasing. In this manipulation, when entering the overloaded-vehicle checkpoint, all axles of the vehicle are lowered to pass normally, and when driving on the main road, the variable axle of the vehicle is illegally lifted with the axle load exceeding 10 tons alarmingly. Therefore, this study developed a technology to detect the state of the variable axle of a truck driving on the road using roadside camera images. In particular, this technology formed the basis for cracking down on overloaded vehicles by lifting the variable axle after entering the checkpoint and linking the vehicle with the account information of the checkpoint. Fundamentally, in this study, the tires of the vehicle were recognized using the Mask RCNN algorithm, the recognized tires were virtually arranged before and after the checkpoint, and the height difference of the vehicle was measured from the arrangement to determine whether the variable axle was lifted after the vehicle left the checkpoint.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.30-41
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• 2022

With the advent of autonomous driving, personal mobility, drones, and smart roads, it is necessary to respond to changes in the road traffic environment in the road guidance system. However, the use of road signs to guide the road is decreasing compared to the past due to the advent of devices such as navigation and smartphones. Therefore, in this study, a large-scale survey was conducted to derive road sign issues and usage plans to respond to future changes. Based on this, this study presented a strategy to diversify road sign functions by analyzing the factors affecting the use of road signs by citizens. As a result, first, it is necessary to provide real-time variable road guidance information that reflects user needs such as traffic, weather, and local events. Second, it is necessary to informatize digital road signs such as reflecting maps with precision. Third, it is necessary to demonstrate road guidance in a virtual environment that reflects various future mobility and road environments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.64-79
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• 2023

This study reviewed the process of applying the Monte Carlo simulation technique to the traffic allocation problem of metropolitan subways. The analysis applied the assumption of a normal distribution in which the travel time information of the inter-station sample is the basis of the probit model. From this, the average and standard deviation are calculated by separating the traffic between stations. A plan was proposed to apply the simulation with the weights of the in-vehicle time of individual links and the walking and dispatch interval of transfer. Long-distance traffic with a low number of samples of 50 or fewer was evaluated as a way to analyze the characteristics of similar traffic. The research results were reviewed in two directions by applying them to the Seoul Metropolitan Subway Network. The travel time between single stations on the Seolleung-Seongsu route was verified by applying random sampling to the in-vehicle time and transfer time. The assumption of a normal distribution was accepted for sample sizes of more than 50 stations according to the inter-station traffic sample of the entire Seoul Metropolitan Subway. For long-distance traffic with samples numbering less than 50, the minimum distance between stations was 122Km. Therefore, it was judged that the sample deviation equality was achieved and the inter-station mean and standard deviation of the transport card data for stations at this distance could be applied.