• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.39-40
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• 2022

최근 전동 킥보드, 전동휠, 전기 자전거 등 개인형 이동수단(Personal Mobility)의 보급이 늘면서 관련 인명 교통사고가 급증하고 있다. 본 논문에서는 개인형 이동수단의 사용위험 및 사고 감소를 목적으로, 딥러닝 객체탐지 기술을 적용하여 다양한 위험요소를 증강현실 기술을 기반으로 한 HMD(Helmet mounted display)에 표시하는 '딥러닝 객체 인식과 증강현실을 적용한 개인 이동장치를 위한 HMD(Helmet Mounted Display) 어플리케이션'을 설계한다. 제시하는 방법은 실시간으로 수집된 전방의 실시간 영상 정보를 객체 탐지 알고리즘을 통해 위험요소 및 안전한 주행을 보조하는 객체를 감지하고 증강현실을 적용해 사용자에게 적절한 운전 보조장치 및 기능을 제공한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.1 s.12
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• pp.13-26
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• 2007

A VDS data in the domestic has been used within limits to real time information such as congestion management, incident management, and route guidance service. On the other hand, a VDS data in the foreign countries had been used to various objectives such as transportation policy assessment, transportation construction evaluation, franc safety improvement, and etc. The scope and method of the study is the VDS data which was installed in the uninterrupted flow such as the freeway and the interrupted flow in a diversion route of the leeway. It has investigated and analyzed the VDS as our subject to study, study objective and study methodology for each study generally classified as 1) data collection 2) data processing 3) data store and 4) data quality section. This study has investigated and analyzed the various literatures in domestic and foreign countries regarding the VDS data. And It drew the development direction of the study which is about VDS data in domestic from now.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.147-155
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• 2005

The purpose of this paper is to develop a method for estimation of reliable path-travel time using data obtained from the toll collection system on freeways. The toll collection system records departure and arrival time stamps as well as the identification numbers of arrival and destination tollgates for all the individual vehicles traveling between tollgates on freeways. Two major issues reduce accuracy when estimating path-travel time between an origin and destination tollgate using transaction data collected by the toll collection system. First, travel time calculated by subtracting departure time from arrival time does not explain path-travel time from origin tollgate to destination tollgate when a variety of available paths exist between tollgates. Second, travel time may include extra time spent in service and/or rest areas. Moreover. ramp driving time is included because tollgates are installed before on-ramps and after off-ramps. This paper describes an algorithm that searches for arrival time when departure time is given between tollgates by a Progressive Iterative Forward and Backward (PIFAB) search method. The algorithm eventually produces actual path-travel times that exclude any time spent in service and/or rest areas as well as ramp driving time based on a link-based procedure.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.686-693
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• 2014

This study presents a model that enables to predict road surface temperature using neural network theory. Historical road surface temperature data were collected from Road Weather Information System. They used for the calibration of the model. The neural network was designed to predict surface temperature after 1-hour, 2-hour, and 3-hour from now. The developed model was performed on Cheongwon-Sangju highway to test. As a result, the standard deviation of the difference of the predicted and observed was $1.27^{\circ}C$, $0.55^{\circ}C$ and $1.43^{\circ}C$, respectively. Also, comparing the predicted surface temperature and the actual data, R2 was found to be 0.985, 0.923, and 0.903, respectively. It can be concluded that the explanatory power of the model seems to be high.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.153-172
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• 2018

Overloading of Commercial vehicles have been an important area of transportation as one of the main causes of pavement damage, bridge collapse, severe traffic accident, etc. In this study, we analyzed the effects of overweight prevention by analyzing overweight driving patterns and using weight sensors. First, we analyzed relevant literatures of overweight and surveyed the commercial weight sensors. Then we chose the typical type of overweight vehicles based of overweight enforcement data analysis. MEMs inclinometer weight sensor were installed to 10 test vehicles and data was collected by weight sensors and gps in real time. As a result of gross vehicle weight and axle weight analysis, it was found weight sensor could decrease overweight rate. However, since the number of samples of test vehicles is insufficient to represent the whole commercial vehicle, further studies are deemed possible through the extension test.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.131-142
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• 2023

In this paper, we propose a new station selection algorithm to solve the illegal parking problem of shared electric scooters and improve the service quality. Recently, as a solution to the urban transportation problem, shared electric scooters are attracting attention as the first and last mile means between public transportation and final destinations. As a result, the shared electric scooter market grew rapidly, problems caused by electric scooters are becoming serious. Therefore, in this study, text data are collected to understand the nature of the problem, and the problems related to shared scooters are viewed from the perspective of pedestrians and users in 'LDA Topic Modeling', and a station extension algorithm is based on this. Some parking lots have already been installed, but the existing parking lot location is different from the actual area of tow. Therefore, in this study, we propose an algorithm that can install stations at high actual tow density using mixed clustering technology using K-means after primary clustering by DBSCAN, reflecting the 'current state of electric scooter tow in Seoul'.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.357-362
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• 2023

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2007.10a
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• pp.169-175
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• 2007

고리, 월성, 울진, 영광 등4개 원전부지와 하나로 연구용 원자로 부지에 대해 방사성물질의 대기 중 누출사고 발생 시 대축척 전자지도와 연계한 사고정보 파악, 예상피해분석, 방재시설 및 소개정보 활용 등을 통해 중앙정부 및 지방자치단체가 방사능 물질 피해지역관리 및 신속하고 효율적인 주민대응조치 수립을 위한 의사 결정 지원할 수 있는 방사능방재 지리정보시스템 구축이 필요하다. 본 연구에서는 고리, 월성, 울진, 영광, 대전지역의 원자력 발전소 및 연구용 원자로 반경 40km이내 지역의 행정경계, 도로, 등고, 수계, 건물 등의 일반지형지물정보와, 비상계획구역 내 마을의 상세정보, 집결지, 대피소, 교통통제소, 환경방사능감시기, TLD등의 방재시설물 위치 및 관련 상세정보, 관공서, 경찰서, 소방서, 보건소, 학교, 병원 등의 방재관련 지형지물 위치 및 관련 상세정보, 원전부지 내 인구분포, 보유 차량 분포, 농작물 재배 현황, 축산물 재배현황 등의 방재관련 사회통계정보를 포함하는 공간 및 속성 데이터베이스는 구축하였다. 이를 기반으로 방사선 피폭영향 평가시스템(FADAS)의 예상평가결과를 전자지도 상에 표출하고, 이에 근거한 예상피해를 분석하며, 소개단계 대상 마을 검색 및 바람장 분석을 활용한 소개경로 제시 등을 통해 주민보호조치 의사결정을 지원하며, 사고대응 및 소개현황 정보를 관리하는 웹 기반의 원자력방재 지리정보시스템을 확대 개발하였다. 방재시설물 및 방재관련 지형지물, 방재관련 사회통계자료의 검색기능 및 실시간 원전 바람장 정보조회, 실시간 ERMS 수집정보 조회, 수치예보 정보 조회, 온라인DB관리 등의 확대 구현을 통해 사고대응조치 및 피해분석업무를 지원하였다. 본 연구를 통한 원자력방재 지리정보시스템 완성을 통해 방사능 비상시 중앙본부와 지역본부 및 유관기관 간에 지리정보와 연계한 정확한 사고정보 및 방재정보의 신속한 공유를 제공하고, 적절한 비상대응조치 의사결정 및 주민보조조치 수행을 지원하여 효율적인 사고지역 관리 및 인적 물적 자원의 피해를 최소화하는데 기여할 것으로 기대된다.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.259-270
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• 2021

Recently, interests in the use of Sharing Bike is increasing in consideration of eco-friendly transportation and safety from viruses. As the technology for collecting and storing data is improved with the development of ICTs, research on mobility using the Sharing Bike Data is also actively progressing. Therefore, this paper analyzes the properties of Sharing Bike Data and cases of researches on it through literature review, and based on the results of the review, data of Eoulling, the Sharing Bike System of Sejong City is analyzed as a way to utilize Sharing Bike Data. Most of the selected literature used structured data, and analyzed it through statistical methods or data mining. Through data analysis, it identified the current status, found out problems of the Sharing Bike System, proposed a solution to solve them, developed plans to activate the use of Sharing Bike. This provides basic data for efficient management and operation plans for Sharing Bike System. Ultimately, it will be possible to explore ways to improve mobility in urban spaces by utilizing Sharing Bike Data.