• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.57-70
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• 2012

Variable speed limit(VSL) is a useful speed management tool for alleviating traffic congestion and enhancing traffic safety. The purpose of this study is to identify promising freeway segments for safety enhancement through VSL operations. An ordered probit model was adopted to capture factors affecting freeway crash severity that can be used to support decision making for selecting the promising segments. Pseudo elasticity and marginal effects, which are outcomes of the ordered probit analysis, were used to determine priority of promising segments for traffic safety. The results of this study would be useful in installing VSL systems and developing traffic control and operations strategies in practice.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.127-137
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• 2006

This Paper Presents a novel incident detection method for using the speed-density difference between detectors. When a incident is happened the downstream traffic condition is mostly lower speed and higher density and the upstream is higher speed and lower density In respect of such characteristics, we can suggest a method for detecting an incident based on the speed-density information provided from detectors. The incident detection method is tested by using the accident data collected from the Cheonan-Nonsan Highway. The results show that suck an incident detection method can analyze the position of accident by comparing the speed-density difference between detectors. The work described in this paper is only at on early stage, in the sense that there are several areas to be further investigated in application of this method. such as setting a critical value for judging the incident. a level of accident wave, a varying Pattern between the incident locations and detectors, etc.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.89-95
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• 2008

In this paper, we propose an integrated techniques for managing data quality in traffic data warehousing environments. We describe how to collect and construct the traffic data warehouses from the operational databases, such as FTMS and ARTIS. We explain how to configure the traffic data warehouses efficiently. Also, we propose a quality management techniques to provide high quality traffic data for various analytical transactions. Proposed techniques can contribute in providing high quality traffic data to the traffic related users and researcher, thus reducing data preprocessing and evaluation cost.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.290-292
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• 2007

현재 한국도로공사에서 운영하는 고속도로 교통관리시스템(FTMS)과 우회도로 교통정보시스템(ARTIS)은 차량 검지 장치와 CCTV 를 통해 실시간 교통 자료를 수집하고, 도로전광표지(VMS), 방송, 인터넷 등 다양한 매체로 교통 정보를 제공하는 시스템이다. 이러한 시스템들은 매일 도로에서 수집되는 엄청난 양의 교통 자료를 실시간 교통 정보 제공하는데 목적을 두고 있어, 교통 자료를 가공하고 처리하여 분석을 수행하는 연구 환경을 제공하는데 어려움이 많다. 본 논문에서는 여러 시스템으로부터 대용량의 교통 자료를 가져와 하나의 통합 데이터베이스로 구축하고, 이를 통해 얻은 교통 이력 자료를 연구할 수 있는 환경을 제안한다.

• 한국디지털정책학회:학술대회논문집
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• 2004.05a
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• pp.593-608
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• 2004

우리나라의 경우 교통정보수집용 검지기는 루프검지기가 주종을 있으며, 지금까지 한국에서 루프검지기를 대체할 수 있는 영상 및 초단파검지기와 같은 대체검지기에 대한 평가는 단속류 보디는 연속류 상황에 대한 평가로 제한되어 왔다. 한편 최근들어 점차 고속도로를 중심으로 영상검지기의 설치개소수가 급속히 증가하고 있는 추세이다. 이 영상검지기의 경우 연속 교통류 상황의 15 분 혹은 5 분 단위의 점유율, 교통량, 속도등의 교통변수 측정정확도는 검지시스템의 요구사항을 충족하는 것으로 나타났다. 본 연구에서는 한국의 장래 교통관리 첨단화에 요구되는 교통자료 수집수준을 시가지도로 및 고속도로를 중심으로 파악하고, 루프검지기의 대체 검지기로서 영상검지기에 대한 성능평가 및 분석을 실시하였다.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.29-37
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• 2006

As a recurrent congestion of urban freeway occurs in almost same time and section, it is possible to manage the congestion effectively by the expectation and advance correspondence. In the existing traffic management system. we have used pattern data to manage a recurrent congestion. But it is not applicable to an urban freeway which kas various traffic circumstance. In this study, the probability by travel speed using a statistical distribution method will be used to predict the probability of recurrent congestion. It is expected that we can get the point of time and the duration of recurrent congestion, and we can devise an effective advance correspondence and a transportation operation.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.177-185
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• 2011

In order to reduce traffic accidents at long road sections involving high risks of traffic accidents, including tunnels, bridges or curves, the National Police Agency have decided a tentative installation and operation of an automated point-to-point speed enforcement system based on cameras at January, 2007. The first system was established at the direction to Kangreung of Dunnae Tunnel at December, 2007. Currently, the automated point-to-point speed enforcement system operates at 11 sections including eight sections on expressways and three sections on national highways. However, there have been few researches on the effects of the system upon the reduction of traffic accidents in a scientific way. To this end, this research effort was initiated to evaluate the effect of the automated point-to-point speed enforcement system on traffic safety by comparing the number of traffic accidents before and after the installation of the system using a comparison-group(C-G) method. Three-year-long traffic accident data for the expressways were collected in order to evaluate the system. As a result, the installation of the system was found to reduce traffic accidents by 49.97% in average.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1123-1130
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• 2020

This study aims to classify the severity in car crashes using five classification learning models. The dataset used in this study contains 21,013 vehicle crashes, obtained from Korea Expressway Corporation, between the year of 2015-2017 and the LightGBM(Light Gradient Boosting Model) performed well with the highest accuracy. LightGBM, the number of involved vehicles, type of accident, incident location, incident lane type, types of accidents, types of vehicles involved in accidents were shown as priority factors. Based on the results of this model, the establishment of a management strategy for response of highway traffic accident should be presented through a consistent prediction process of accident severity level. This study identifies applicability of Machine Learning Models for Predicting of the Severity of Car Traffic Accidents on a Highway and suggests that various machine learning techniques based on big data that can be used in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.685-691
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• 2009

The purpose of this paper is to classify the traffic condition in freeway by the impacts of road weather. The factor analysis showed that weather factors, which are considered as influential, are identified as weather condition (rain or clear), temperature and sight distance with RWIS and VDS data in Seohae bridge used. The result of ANOVA shows that weather is dividedinto clear and rainy; temperature into below and equal or above $5^{\circ}C$ and sight distance into below or equal or above 10km. Based on those factors, the freeway traffic condition has been classified as five different types. The flow-speed model for each traffic conditions was proposed, which was not significant due to the lack of smaple data. Although not sufficient, the methodology to categorize traffic situation model presented in this paper may shed light on the idea for the future and can be used for proper traffic management for each weather condition.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.458-467
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• 2017

The expressway of the Korea has an important role in freight movement because 76 percent of the commodity is transported by trucks. However, there has been few indices on the role of expressways regarding freight transportation and truck traffic. The objective of this study is to propose four freight transportation related indices using ITS-related system such as TCS and HS-Wim: total truck's travel miles ($veh{\cdot}km/year$), total freight transport miles ($ton{\cdot}km/year$). efficiency of truck's travel ($veh{\cdot}km/km$), and efficiency of freight movement ($ton{\cdot}km/km$). These truck and freight related indices were estimated and compared by two different data sources: traffic volume data using VDS and OD data using TCS. These indices were designed to estimated on real time and updated every day and month.