• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.5
• /
• pp.182-199
• /
• 2023

Since 2021, government departments have been promoting Automated Driving Technology Development and Innovation Project as national research and development(R&D) project. The automated vehicles and service technologies developed as part of these projects are planned to be subsequently provided to the public at the selected Living Lab City. Therefore, it is important to determine a spatial area and operation section that enables safe and stable automated driving, depending on the purpose and characteristics of the target service. In this study, the static Operational Design Domain(ODD) elements for Level 4 automated driving services were reclassified by reviewing previously published papers and related literature surveys and investigating field data. Spatial analysis techniques were used to consider the reclassified ODD elements for level 4 in the real area of level 3 automated driving services because it is important to reflect the spatial factors affecting safety related to real automated driving technologies and services. Consequently, a total of six driving mode changes(disengagement) were derived through spatial information analysis techniques, and the factors affecting the safety of automated driving were crosswalk, traffic light, intersection, bicycle road, pocket lane, caution sign, and median strip. This spatial factor analysis method is expected to be useful for determining special areas for the automated driving service.

• Korean Security Journal
• /
• no.61
• /
• pp.285-305
• /
• 2019

In the bill of [Act on Certified Detective and Certified Detective Business] (hereinafter referred to as the Certified Detective Act) proposed and represented by the member of National Assembly, Lee Wan-Yong in 2017, the legislative point of view showed that various incidents and accidents, including new crimes, are frequently increasing as society develops and becomes more complex, however, it is not possible to solve all the incidents and accidents with the investigation force of the state alone due to manpower and budget, and therefore, a certified detective or private investigator are required. According to the decision of the Constitutional Court in June 2018, Article 40 (4) of the Act on the Use and Protection of Credit Information is concerned with 'finding the location and contact information of a specific person or investigating privacy other than commerce relations such as financial transactions' are prohibited. It is for the purpose of preventing illegal acts in the process of investigation such as the location, contact information, and the privacy of a specific person and protecting the privacy and tranquility of personal privacy from misuse and abuse of the personal information etc. Such 'privacy investigation business' currently operates in the form of self-employment business, which becomes a social issue as some companies illegally collect and provide such privacy information by using illegal cameras or vehicle location trackers and also comes to be the objects of clampdown of the investigative agency. Considering this reality, because it is difficult to find a resolution to materialize the legislative purpose of the Act on the use and protection of credit information other than prohibiting 'investigation business including privacy etc' and it is possible to run a similar type of business as a detective business in the scope that the laws of credit research business, security service business, the position of the Constitutional Court is that 'the ban on the investigations of privacy etc' does not infringe the claimant's freedom to choose a job. In addition to this decision, the precedent positions of the Constitutional Court have been that, in principle, the legislative regulation of a particular occupation was a matter of legislative policy determined by the legislator's political, economic and social considerations, unless otherwise there were any special circumstances, and. the Constitutional Court also widely recognized the legislative formation rights of legislators in the qualifications system related to the freedom of a job. In this regard, this study examines the problems and improvement plans of the certified detective system, focusing on the certified detective bill recently under discussion, and tries to establish a legal basis for the certified detective and certified detective business, in order to cultivate and institutionalize the certified detective business, and to suggest methodologies to seek for the development of the businesses and protect the rights of the people.

• Journal of the Society of Disaster Information
• /
• v.20 no.2
• /
• pp.339-350
• /
• 2024

Purpose: This study analyzes accessibility of 10 hydrogen charging stations in Seoul and identifies areas that were difficult to access. The purpose is to re-analyze accessibility by adding a new location in terms of equity and safety of location placement, and then draw implications by comparing the improvement effects. Method: By applying the location-allocation model and the service area model based on network analysis of the ArcGIS program, areas with weak access were identified. The location selection method applied the 'Minimize Facilities' method in consideration of the need for rapid arrival to insufficient hydrogen charging stations. The limit distance for arrival within a specific time was analyzed by applying the average vehicle traffic speed(23.1km/h, Seoul Open Data Square) in 2022 to three categories: 3,850m(10minutes), 5,775m(15minutes), 7,700m(20minutes). In order to minimize conflicts over the installation of hydrogen charging stations, special standards of the Ministry of Trade, Industry and Energy applied to derive candidate sites for additional installation of hydrogen charging stations among existing gas stations and LPG/CNG charging stations. Result: As a result of the analysis, it was confirmed that accessibility was significantly improved by installing 5 new hydrogen charging stations at relatively safe gas stations and LPG/CNG charging stations in areas where access to the existing 10 hydrogen charging stations is weak within 20 minutes. Nevertheless, it was found that there are still areas where access remains difficult. Conclusion: The location allocation model is used to identify areas where access to hydrogen charging stations is difficult and prioritize installation, decision-making to select locations for hydrogen charging stations based on scientific evidence can be supported.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.47-73
• /
• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.