• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.1-9
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• 2014

This study deals with development of Integrated Transportation Analysis System for Large-scale event. Based on case studies, the requirements of the system were defined and the direction of development was established. The large-scale events that require fast and accurate transportation policy were selected. The data warehouse and data mart were developed by integrating the large-scale event data and the traffic data. Business intelligence system was designed and developed users to allow timely decisions.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.69-70
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• 2015

본 논문에서는 운행중인 차량이 수집한 위치별 교통 이벤트 (지체, 정체, 사고, 노면상태 등)를 다른 운행 차량과 실시간으로 공유하여 안전운행 서비스를 제공하기 위한 방법을 제안한다. 운행중인 차량은 차량내의 스마트 기기나 전용 기기를 이용해 수집한 교통이벤트를 실시간으로 서버로 전송하고 서버는 전송된 교통이벤트를 위치별, 시간별로 색인하고 중복된 교통이벤트를 분류하여 저장한다. 이런 모든 과정은 처리 속도 향상을 위해 Spark의 RDD를 이용해서 인-메모리에서 처리된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.987-994
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• 2018

In this paper, an automatic transmission system of traffic information is presented. Here, a traffic event is defined as an obstacle to an emergency vehicle such as an ambulance or a fire truck. When a traffic event is detected from a video recorded by a black box installed in a vehicle, the implemented system automatically transmits a proof image and corresponding information to the control center through an e-mail. For this purpose, we realize an algorithm of identifying the numbers and a character from the license plate, and an algorithm for determining the occurrence of a traffic event. To report the event, a function for automatic transmission of the text and image files through e-mail and file transfer protocol (FTP) is also appended. Therefore, if the traffic event is extended and applied to the presented system, it will be possible to establish a convenient reporting system for the violation of various traffic regulations. In addition, it will contribute to significantly reduce the number of traffic violations against the regulations.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.83-93
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• 2022

Research is underway to solve the traffic problem by using crowdsourcing, where drivers use their mobile devices to provide traffic information. If it is used for traffic event detection through crowdsourcing, the task of collecting related data is reduced, which lowers time cost and increases accuracy. In this paper, we propose a scheme to collect traffic-related data using crowdsourcing and to detect events affecting traffic through this. The proposed scheme uses machine learning algorithms for processing large amounts of data to determine the event type of the collected data. In addition, to find out the location where the event occurs, a keyword indicating the location is extracted from the collected data, and the administrative area of the keyword is returned. In this way, it is possible to resolve a location that is broadly defined in the existing location information or incorrect location information. Various performance evaluations are performed to prove the superiority and feasibility of the proposed scheme.

• Transportation Technology and Policy
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• v.3 no.1
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• pp.67-79
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• 2006

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• Transportation Technology and Policy
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• v.9 no.3
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• pp.93-99
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• 2012

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.17-18
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• 2019

이 논문에서는 운전자들의 궤적을 예측하여 해당 도로의 돌발 이벤트와 같은 교통정보를 실시간으로 제공하기 위한 방법을 제안한다. 이를 위해서 운전자의 위치 데이터 수집 및 교통 정보 제공의 처리율을 높일 수 있는 이동 객체 및 교통 정보 관리 방법을 제안한다.

• 한국ITS학회:학술대회논문집
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• v.2006 no.10
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• pp.113-117
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• 2006

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 2014.10a
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• pp.44-46
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• 2014