• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.8
• /
• pp.2126-2133
• /
• 2009

As expected that a robot-industry will grow up rapidly toward a huge market, many countries try to develop the official policies to support a robot-industry. Following this trend, many robot researches are proceeded in the various technical areas by the government-initiated R&D strategies in Korea. These R&D programs are archived by academic-industrial collaboration and furthermore, include the disseminated linkage of academic-industrial collaboration and the human resource development program which pursues the problem solving and technical training for companies suffered by several technical difficulties. This paper shows the several analyses and considerations of provisional results of these collaboration programs. First, each program of specialized plan for next generation is reviewed and the accomplishment of human resource development for robot research is evaluated. Finally, several considerations are represented for continuous and desirable expansion of these programs.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.2
• /
• pp.102-110
• /
• 2016

After Sewol ferry disaster occurred in April 2014, Korean government began investing to deploy LTE-based public safety network until the year of 2017. In order to reduce the operating and capital costs, resource sharing scheme among public safety network and commercial LTE networks is considered as one of the viable approaches. This thesis proposes a method of allocating bandwidth of public safety network based on various priorities required for disaster scenarios and stages in a resource sharing environment. In order to obtain the highest efficiency, we formulate the bandwidth allocation problem as a Fractional Knapsack Problem. Greedy algorithm was applied to solve the problem. For performance evaluation, we created several disaster scenarios and set suitable parameters for each scenario based on a disaster manual. The proposed method is compared with two typical methods, which are Class-based bandwidth allocation and Uniform bandwidth allocation. The results showed that the better performance in terms of the sum of the values and the amount of lost bytes.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.2
• /
• pp.24-35
• /
• 2016

Emergency Vehicle Preemption(EVP) is an operation method which helps to improve response condition of Emergency Vehicle(EV) and it has not yet been introduced in Korea. In order to implement the system, it requires step-by-step plan and selecting a priority area for trial operation. Since a municipal government such as Seoul is too large so it is limited in time and cost to analyze the whole area. Therefore, quantitative and effective selection method for priority area is critical. The aim of this study is to propose a selection method of implementation area for EVP system using the dispatch data analysis. This study also determined the priority area for EVP implementation by analyzing the dispatch data in Seoul and conducted a simulation to evaluate the effects of implementing EVP.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.1
• /
• pp.83-90
• /
• 2019

LED lighting is spreading on the strength of LED lighting, and various government policies are being implemented. VLC research which is a wireless communication technology using lighting has been actively conducted, and it has been proven through many studies that a general LED light source such as a high-speed data transmitter can be used. But from now on, one of the main problems is the noise from side lights, which can be compared to the noise of radio broadcasts. So in this paper, we proposed a noise canceling model to remove the interference of ambient light by using an optical filter for a detachable VLC channel. In order to verify the proposed model, various high brightness RGB LED modules were used for comparative analysis. In addition, the applicability was verified through experiments using High Luminance LED lighting which is applied in real life.

• Journal of Internet Computing and Services
• /
• v.22 no.3
• /
• pp.17-26
• /
• 2021

Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at home is also increasingsingle-person households are less likely to be notified to the outside world in times of emergency than multi-person households. This study collects various situations occurring in the home with lidar, image, and voice sensors and analyzes the data according to the sensors through their respective algorithms. Using this method, we analyzed abnormal patterns such as emergency situations and conducted research to detect abnormal signs in humans. Artificial intelligence algorithms that detect abnormalities in people by each sensor were studied and the accuracy of anomaly detection was measured according to the sensor. Furthermore, this work proposes a fusion method that complements the pros and cons between sensors by experimenting with the detectability of sensors for various situations.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.5
• /
• pp.233-252
• /
• 2022

Recently, various studies have been conducted to improve automated vehicle (AV) safety for AVs commercialization. In particular, the scenario method is directly related to essential safety assessments. However, the existing scenario do not have objectivity and explanability due to lack of data and experts' interventions. Therefore, this paper presents the AVs safety assessment extended scenario using real traffic accident data and vision transformer (ViT), which is explainable artificial intelligence (XAI). The optimal ViT showed 94% accuracy, and the scenario was presented with Attention Map. This work provides a new framework for an AVs safety assessment method to alleviate the lack of existing scenarios.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.194-210
• /
• 2022

The user-centered EV charging infrastructure construction policy the government is aiming for can increase convenience for electric vehicle users and bring new electric vehicle users into the market. This study was conducted to provide an in-depth understanding of the charging behaviors of actual electric vehicle users, which can be used as basic information for the electric vehicle charging infrastructure. Based on charging diary data collected for a week, the charging of electric vehicles was analyzed on a daily and weekly basis, and sequence analysis and latent class analysis were used. As a result, five daily charging profiles and four weekly charging profiles were identified, which are expected to contribute to revitalizing the electric vehicle market by providing key information for decision-making by potential electric vehicle users as well for establishing user-centered charging infrastructure policies in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.4
• /
• pp.114-131
• /
• 2023

Personal Mobility (PM)-related accidents have increased rapidly since PM use was activated. In response to the increase in these accidents, the government strengthened regulations for PM users on May 13, 2021. The number of the accidents in which the PM user was a victim decreased significantly. In contrast, the increasing number of accidents in which PM user was the offender did not decrease significantly. In most of these accidents, the PM user was the offender who crashed into pedestrians. Hence, the safety of pedestrians is threatened. Therefore, this study analyzed the factors, such as the regulations, urban built environment, and personal characteristics, affecting the severity of PM-pedestrian accidents by focusing on PM-pedestrian crashes. This study analyzed the PM-pedestrian accidents in Seoul from 2020 to 2021 using binary logistic regression model. Through these results, this study proposed the policy implications.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.1
• /
• pp.123-140
• /
• 2022

Even though driving behaviors in underground roads can be significantly different from ground roads, existing underground roads follow the design guidelines of ground roads. In this context, this study investigates the driving behaviors of the exit-ramp terminal of urban underground roads using a driving simulator. Virtual driving experiments were performed by analyzing scenarios between the underground and ground road environments. The experiments' driving behavior data for each geometry section are compared and validated through a statistical significance test. This test showed that the speed in the underground road environment is relatively low, and the LPM tends to move away from the adjacent tunnel wall. Based on these findings, this study suggests implications and feasible solutions for improving driver's safety in the exit-ramp terminal of the underground roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.49-65
• /
• 2023

In response to the growing global concern for the environment, the international community has recently committed to achieving 'carbon neutrality.' As a result, numerous studies have been conducted on mode choice models that include carbon emissions as a variable. However, few studies have established a correlation between individual preferences and carbon emissions. In this study, a new mode of transportation named sustainable public transit (SPT), incorporating carbon-reducing transport options like electric scooters, is proposed. Analyzing the individual preferences of commuters on carbon emissions through factor analysis, a stated preference (SP) survey was conducted. A mode choice model for SPT was constructed using multinomial logit models. The results of the analysis showed that gender, income, and specific preferences, such as a passion for exploring new routes, a preference for intermodal transfers, knowledge of carbon reduction, and carbon reduction practices, significantly influence latent preferences for SPT. Therefore, this study is significant as it considers carbon emissions as an attribute variable during the construction of mode choice models and reflects the individual preference variables associated with carbon reduction.