• Journal of Environmental Science International
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• v.30 no.1
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• pp.11-17
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• 2021

This research was conducted to propose the basic direction of a smart city plan for the satisfaction of residents of Gangwon-do. Initially, the awareness of smart cities among the residents of Gangwon-do was as follows: The response "I have no idea" was 21.7% higher and "I do not know the details, but have heard of it" was 15.1% lower than the awareness among residents across the nation. Based on these results, it was confirmed that awareness was very low despite the government's smartification reinforcement policy. In addition, the residents of Gangwon-do expected that their time would be saved and their living convenience would increase but were worried that their privacy would be invaded and that the conflict between generations would intensify. Thus, it is necessary to develop a plan to enhance the awareness of smart cities, as well as a plan to enhance digital awareness. Second, based on the importance of and satisfaction with the urban problem response system examined among the residents of Gangwon-do, it seems necessary to prioritize improvements in public space control and administrative problem responses involving deteriorated parks/plazas, pedestrian environment, and administrative processing inefficiency and fairness. Additionally, the first prioritization priority of the residents of Gangwon-do was "health/welfare/medical service" (27.7%); the second and third highest priorities were "transportation service" (26.3%) and "environmental service" (19.0%), respectively. In particular, as "transportation service" was highly preferred in the Chuncheon and Wonju regions and "health/welfare/medical service" was highly preferred in the Gangneung, Sokcho, and other southern regions, it was confirmed that the level of urbanization is deeply associated with smart services.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.4
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• pp.61-75
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• 2021

Roadside greenery in the city is not only a means of reducing fine dust, but also an indispensable element of the city in various aspects such as improvement of urban thermal environment, noise reduction, ecosystem connectivity, and aesthetics. However, in studies dealing with the effect of reducing fine dust through trees in existing urban spaces, microscopic aspects such as the adsorption effect of plants were dealt with, structural changes such as the width of urban buildings and streets, and the presence or absence of trees, Impact studies that reflect the actual form of In this study, the effect of greenery composition applicable to urban space on PM2.5 was simulated through the microclimate epidemiologic model ENVI-met, and field measurements were performed in parallel to verify the results. In addition, by analyzing the results of fine dust background concentration, wind speed, and leaf area index, the sensitivity to major influencing variables was tested. As a result of the study, it was confirmed that the fine dust reduction effect was the highest in the case with a high planting amount, and the reduction effect was the greatest at a low background concentration. Based on this, the cost of planting street green areas and the effect of reducing PM2.5 were compared. The results of this study can contribute as a basis for considering the effect of pedestrian space on air quality when planning and designing street green spaces.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.668-674
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• 2022

Machine learning techniques using visual data have high usability in fields of industry and service such as scene recognition, fault detection, security and user analysis. Among these, user analysis through the videos from CCTV is one of the practical way of using vision data. Also, many studies about lightweight artificial neural network have been published to increase high usability for mobile and embedded environment so far. In this study, we propose the network combining the object detection and classification for mobile graphic processing unit. This network detects pedestrian and face, classifies age and gender from detected face. Proposed network is constructed based on MobileNet, YOLOv2 and skip connection. Both detection and classification models are trained individually and combined as 2-stage structure. Also, attention mechanism is used to improve detection and classification ability. Nvidia Jetson Nano is used to run and evaluate the proposed system.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.485-496
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• 2010

An increase in number of vehicles owned by individuals worsens the conditions of parking in residential areas. So to speak, the pedestrians' safety is seriously threatened by illegally parked vehicles on the residential area roads. As a result, the number of vehicle-to-pedestrian accidents has been increasing annually. Also, illegal parking on arterial roads is increasingly becoming common, especially by cooommercial trucks. However, no solution has been found to reduce or eliminate accidents caused by vehicles illegally parked on readside. The result of this study provides the solutions to enhance the safety of residential area roads and arterial roads, from viewpoints of both long-term and short-term, by collecting data about the status of illegal parking and addressing critical problems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.216-223
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• 2023

As the technology and level of autonomous vehicles advance and they drive in more diverse road environments, an intuitive and efficient interaction system is needed to resolve and respond to the situations the vehicle faces. The development of driving technology from the perspective of autonomous driving has the ultimate goal of responding to situations involving humans or more. In particular, in complex road environments where mutual concessions must be made, the role of a system that can respond flexibly through efficient communication methods to understand each other's situation between vehicles or between pedestrians and vehicles is important. In order to resolve the status of the vehicle or the situation being faced, the provision and method of information must be intuitive and the efficient operation of an autonomous vehicle through interaction with intention is required. In this paper, we explain the vehicle structure and functions that can display information about the situation in which the autonomous vehicle driving in a living lab can drive stably and efficiently in a diverse and complex environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.43-52
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• 2023

Traffic accidents among children have been decreasing after the installation of yellow carpets. However, the explanatory power of the causal relationship between yellow carpet installation and traffic accidents is still insufficient. The yellow carpet effect was analyzed in greater depth using virtual reality (VR) simulation experiments in various situation that could not be evaluated in existing actual vehicle research studies due to difficulties or risks in implementation. A target site where an actual yellow carpet was installed was selected and, implemented into a virtual environment. Subjects were made to, were gaze measurement equipment and ride the simulator. The visual/driving behavior before and after yellow carpet installation was compared, and a t-test analysis was performed for statistical verification. All the results were found to be statistically significant.

• Journal of the Korean Regional Science Association
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• v.40 no.1
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• pp.19-35
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• 2024

This research aims to compare and analyze changes in local physical environmental factors affecting mental health before and after the occurrence of COVID-19. The research question is: "Did the influence of environmental factors affecting mental health change after the emergence of the COVID-19 pandemic?" To examine the research question, the study considered the year 2019, right before COVID-19, and the year 2020, the year when COVID-19 occurred, as the temporal scope of the research. For the empirical analysis, we used multilevel logistic analysis was conducted using data from the Community Health Survey for each year and the National Statistical Office (KOSIS). The results can be summarized as follows: After the occurrence of COVID-19, physical environmental factors showed stronger associations with mental health compared to before the emergence of COVID-19. Specifically, it was found that park area per thousand people and the proportion of pedestrian-only road areas were further associated with a decrease in depression. Based on these findings, this study suggests the need for improving and constructing the physical environment in local communities for preventing mental health issues during disaster situations such as COVID-19.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.67-75
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• 2024

Crosswalks play an important role for the safe movement of pedestrians in a complex urban environment. However, for the visually impaired, crosswalks can be a big risk factor. Although assistive tools such as braille blocks and acoustic traffic lights exist for safe walking, poor management can sometimes act as a hindrance to safety. This paper proposes a method to improve accuracy in a deep learning-based real-time crosswalk detection model that can be used in applications for pedestrian assistance for the disabled at the beginning. The image was binarized by utilizing the characteristic that the white line of the crosswalk image contrasts with the road surface, and through this, the crosswalk could be better recognized and the location of the crosswalk could be more accurately identified by using two models that learned the whole and the middle part of the crosswalk, respectively. In addition, it was intended to increase accuracy by creating a boundary box that recognizes crosswalks in two stages: whole and part. Through this method, additional frames that the detection model did not detect in RGB image learning from the crosswalk image could be detected.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.4
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• pp.513-518
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• 2024

When introducing a new policy or technology, it is common for both opposing and approving opinions to exist. In particular, identifying factors that influence opposing opinions can be the first step to successfully introducing new policies or technologies. The purpose of this study is to identify the factors affecting the acceptability of tram, a new transportation mode, in urban areas of Jeju. For this purpose, a survey was conducted on 326 Jeju residents and 104 tourists for eight days, and the surveyed data was analyzed for the main factors affecting acceptability using structural equation modeling (SEM). As a result, it was found that the higher the recognition of tram operation characteristics, the more positive the acceptability. In particular, while tram operation in downtown Jeju was evaluated positively from the perspective of the convenience of using public transportation and the urban environment, it was evaluated negatively from the perspective of traffic crashes, congestion, and pedestrian safety due to traffic conflicts. These results are expected to be used as a basis for establishing policies to successfully adopt trams in Jeju City in the future.