• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.1
• /
• pp.109-114
• /
• 2012

Intelligent Transportation Systems (ITS) is aimed to implement IT(Information Technology) to develop the next-generation transportation system in order to improve traffic conditions. In order to provide traffic information, the methods that provide available traffic informations to the public are needed. In this paper, analysis of the transportation applications in smart-phone and currently available methods of traffic information's sharing and providing were discussed. Finally, OPEN API was discussed and shows its effectiveness for transportation information area especially in smart phone.

• Smart Media Journal
• /
• v.11 no.11
• /
• pp.49-62
• /
• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• Broadcasting and Media Magazine
• /
• v.24 no.1
• /
• pp.49-55
• /
• 2019

최근 수년간 급속도로 발전한 정보통신(ICT) 및 인공지능(AI) 관련 기술은 사회전반에 걸쳐 모든 산업영역에 변화의 바람을 불러일으키고 있다. 교통부문에서도 이러한 기술의 융 복합을 통해 교통체계의 효율성과 안전성을 향상시키기 위한 노력이 자율주행의 기술발전으로 나타나고 있다. 자율주행은 그동안 인간이 운전해오던 자동차 중심의 교통체계에 혁신적인 변화의 동인이 될 것으로 전망된다. 개인 승용차 시장에 자율주행자동차의 등장과 버스, 택시 등 대중교통과 공유교통차량의 대중교통 기능 적용, 그리고 트럭 및 대형버스 등 상용차의 군집주행기술 도입 등 다양한 분야에서 산업화가 진행되고 있는 것이 그 이유다. 이로 인해 시민들의 일상생활에서 가장 중요한 부분을 차지하는 이동성(Mobility)을 제공하는 서비스에 상당한 영향을 줄 것으로 예측되고 있다. 본 고는 자율주행이 가져올 미래 교통체계의 변화로 대변되는 스마트 모빌리티에 대한 기술과 서비스 방향에 대해 진단하고, 효율적인 산업화를 위한 방안을 제시한다.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.1
• /
• pp.28-38
• /
• 2019

The smart card data stores the transit usage records of individual passengers. By using this, it is possible to analyze the traffic demand by station and time. However, since the purpose of the trip is not recorded in the smart card data, the demand for each purpose such as commuting, school, and leisure is estimated based on the survey data. Since survey data includes only some samples, it is difficult to predict public transport demand for each purpose close to the complete enumeration survey. In this study, we estimates the purposes of trip for individual passengers using the smart card data corresponding to the complete enumeration survey of public transportation. We estimated trip purposes such as commute, school(university) considering frequency of O-D, duration, and departure time of a passenger. Based on this, the passengers are classified as workers and university students. In order to verify our methodology, we compared the estimation results of our study with the patterns of the survey data.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.1
• /
• pp.163-173
• /
• 2021

In the era of digital transformation, the transportation underprivileged remains as an underprivileged class without the benefits of technological advances. Electric assist devices for the People with disability are inadequate to provide services suitable for the current traffic environment, although the mobility of the People with disability is improved. In this paper, we develop IoT smart mobility by deriving essential elements through user satisfaction surveys to efficiently move physical distances based on the experience of users using existing electric assistive devices. Based on the data collected through user satisfaction survey, quantitative analysis using TF-IFD and qualitative analysis based on QFD are performed to determine the importance of user requirements. For the evaluation of IoT smart mobility design results reflecting essential functions, usability verification is conducted by forming an expert evaluation team in various fields. In the future, we plan to conduct a service design study that can improve mobility convenience and provide mobility service solutions by designing to provide efficient public services by utilizing IoT smart mobility to the People with disability.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.9
• /
• pp.6368-6375
• /
• 2015

The goal of this research is to identify the energy planning techniques of Smart Green City and to establish the realized plan through the analysis of Multi-functional Administrative City. For the research, eighteen planning techniques were derived and categorized into three sectors and six basic direction through literature review and Brain-storming analysis considering correlation between three goals of Smart Green City and expectation of planning technique. And Multi-functional Administrative City was analyzed for the current status of application of planning techniques focus on two application aspects. In conclusion, 'Establishing Integrated Management Center for Urban Energy', 'Building Energy Management System', 'Building Automation System', 'Green Transport System', 'Intelligent Transport System', 'Introduction of Eco-friendly Transportation' planning techniques in reduction of building energy consumption sector and green-intelligent transport system sector were identified as important techniques for Smart Green City.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.6
• /
• pp.144-152
• /
• 2018

This study focuses on collecting traffic data using drones to compensate for limitation of the data collected by the existing traffic data collection devices. Feasibility analysis was performed to verify the traffic data extracted from drone videos and optimal methodology for extracting data was established through analysis of various data reduction scenarios. It was found from this study that drones are very economical traffic data collection devices and have strength of determining the level-of-service(LOS) for uninterrupted flow condition in a very simple and intuitive way.

• Transportation Technology and Policy
• /
• v.6 no.2
• /
• pp.57-68
• /
• 2009

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.11a
• /
• pp.313-314
• /
• 2022

항로표지법은 항로표지를 설치하고 합리적이고 효율적으로 관리하여 해상교통의 안전을 도모하고, 선박 운항의 능률을 향상시키는데 이바지하는 것을 목적하며, 항로표지의 정의와 설치·관리 및 보호, 장비·용품 등의 연구·개발 및 검사 등을 법으로 규정하고 있다. 항로표지는 해상교통의 중요한 인프라로 미래 해상환경 패러다임(MASS, AI Port, Digiral twin 등)에 대응이 가능한 스마트 항로표지로 전향하는 길목에 있다. 스마트 항로표지는 자가 고장진단 및 전원유지, 다중통신 기술 인터페이스를 제공하는 등 다목적 해양플랫폼, 전원관리시스템, 해양용다중통신 플랫폼 등을 국가 R&D를 통해 개발하고 있으며, 국내 해상 실증을 통한 글로벌 표준 제정 등의 과정을 거쳐 최종적으로는 기술이전을 통한 국내 관련 업체들의 해외진출까지를 목표로 하고 있어 기존 항로표지법을 개발될 스마트 항로표지 적용 및 활용·확산을 위한 개선 방안 마련이 필요하다.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.87-96
• /
• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.