• Journal of Korean Society of Transportation
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• v.25 no.1 s.94
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• pp.121-132
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• 2007

Up to now Permanent traffic volumes have been counted by Automatic Vehicle Classification (AVC) on National Highways. When counted data have missing items or errors, the data must be revised to stay statistically reliable This study was carried out to estimate correct data based on outoregression and seasonal AutoRegressive Integrated Moving Average (ARIMA). As a result of verification through seasonal ARIMA, the longer the missed period is, the greater the error. Autoregression results in better verification results than seasonal ARIMA. Traffic data is affected by the present state mote than past patterns. However. autoregression can be applied only to the cases where data include similar neighborhood patterns and even in this case. the data cannot be corrected when data are missing due to low qualify or errors Therefore, these data shoo)d be corrected using past patterns and seasonal ARIMA when the missing data occurs in short periods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.23-30
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• 2006

The variation in the traffic volume on any given roads is the reflection of its user's economic activities and life patterns. And traffic volume flows in every hour usually take different charateristics depending on the location and the function of the roads. This study produced the Monthly Adjustment Factor, Weekly Adjustment Factor and Design hourly Factor, each of which is the index indicating the traffic volume charaterirstics on the highways leading to the recreation areas in the mountainous and seaside tourist sites. Applying these results, it might be possible to calculate the optimal AADT (Annual Average Daily Traffic) and DHV (Design Hour Volume), also be a help to establish a traffic management policy. Finally, it hopes to promote new version of KHCM (Korea Highway Capacity Manual) which includes traffic volume characteristics on recreation areas.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.406-414
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• 2015

Existing relative researches for traffic were studied under favorable weather or excluding impact of weather. This study present traffic volume variation according to rainfall intensity in national highway provincial road and rainfall-factor. Continuous traffic count section match AWS after selecting to analyze provincial road 256 section. Weekdays ADT(Average Daily Traffic) and rainfall-factor are influenced by rainfall a little because of business travel. But non-weekdays ADT and rainfall-factor are influenced much more than weekdays because of leisure travel. Estimated AADT(Annual Average Daily Traffic) by adjusting rainfall-factor is lower MAPE than non-adjusting rainfall factor. So, rainfall have to be considered when estimating AADT. ADT decrease according to rainfall intensity, continuous studies considered rainfall intensity are needed when road design and operation.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.109-121
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• 2007

In this study, an imputation model using circular probability distribution was developed in order to overcome problems of missing data from a traffic survey. The existing ad-hoc or heuristic, model-based and algorithm-based imputation techniques were reviewed through previous studies, and then their limitations for imputing missing traffic volume data were revealed. The statistical computing language 'R' was employed for model construction, and a mixture of von Mises probability distribution, which is classified as symmetric, and unimodal circular probability were finally fitted on the basis of traffic volume data at survey stations in urban and rural areas, respectively. The circular probability distribution model largely proved to outperform a dummy variable regression model in regards to various evaluation conditions. It turned out that circular probability distribution models depict circularity of hourly volumes well and are very cost-effective and robust to changes in missing mechanisms.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.185-190
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• 2007

대용량의 자료가 생산됨에 따라 데이터를 효율적으로 저장, 관리, 이용할 수 있는 데이터 웨어하우스의 역할이 중요하게 되었고, 그에 따라 자료 처리 기법의 개발은 필수 과제가 되었다. 품질 평가와 오류 판단, 결측 보정의 자료 처리 과점은 자료의 신뢰도를 판단하고 활용도를 높일 수 있는 과정으로 매우 중요하다. 본 논문에서는 우리나라의 실제 교통상황을 반영하고 평가 기준의 오차를 줄이면서 더욱 간단 명료한 평가 계산식을 도입하여 효율적인 품질평가와 오류판단, 결측 보정의 자료 처리 기법을 제안한다. 또한 오류 판단 기준에 새로운 파라미터론 도입하여 교통 연구자의 요구 사항을 반영할 수 있게 하였다. 결측 보정 과정은 여러 기법을 연구하고 기존의 결측 보정 기법에 입력 변수를 추가하여 실제 대용량의 교통 자료에 적용하였다. 그리고 교통 자료가 저장되는 데이터베이스에 직접 접근하여 결측 보정과정을 수행하도록 PL/SQL로 구현하였으며, 이를 통해 교통 연구자에게 쉽고 다양한 방법으로 결측 보정을 수행하고 그 결과를 이용하여 다양한 교통 정보를 가공할 수 있는 환경을 제공하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.1-14
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• 2013

Annual average daily traffic (AADT) serves the important basic data in transportation sector. Despite of its importance, AADT is estimated through permanent traffic counts (PTC) at limited locations because of constraints in budget and so on. At most of locations, AADT is estimated using short-term traffic counts (STC). Though many studies have been carried out at home and abroad in an effort to enhance the accuracy of AADT estimate, the method to simplify average STC data has been adopted because of application difficulty. A typical model for estimating AADT is an adjustment factor application model which applies the monthly or weekly adjustment factors at PTC points (or group) with similar traffic pattern. But this model has the limit in determining the PTC points (or group) with similar traffic pattern with STC. Because STC represents usually 24-hour or 48-hour data, it's difficult to forecast a 365-day traffic variation. In order to improve the accuracy of traffic volume prediction, this study used the geostatistical approach called co-kriging and according to their reports. To compare results, using 3 methods : using adjustment factor in same section(method 1), using grouping method to apply adjustment factor(method 2), cokriging model using previous year's traffic data which is in a high spatial correlation with traffic volume data as a secondary variable. This study deals with estimating AADT considering time and space so AADT estimation is more reliable comparing other research.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.115-125
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• 2023

This paper relates to the development of CCTV camera posture calibration algorithm that can simultaneously collect traffic information such as traffic volume and speed in the state of view of the CCTV camera set for traffic monitoring. The developed autonomous posture calibration algorithm uses vehicle recognition and tracking techniques to identify the road, and automatically determines the angle of view for the operator's traffic surveillance and traffic information collection. To verify the performance of the proposed algorithm, a CCTV installed on site was used, and the results of the angle of view automatically calculated by the autonomous posture calibration algorithm for the angle of view set for traffic surveillance and traffic information collection were compared.

• Journal of Korean Society of Transportation
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• v.16 no.3
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• pp.7-14
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• 1998

터널의 경우 도로교통용량이 일반구간에 비해 감소하는 것으로 나타나고 있다. 그러나 연속되는 터널의 경우에 있어 도로교통용량감소에 대한 연구는 아직 이루어지지 않고 있다. 본 연구에서는 고속도로의 2지점에서 연속되는 터널의 도로교통용량의 감소특성을 이용한 터널보정계수를 산정하여 다음과 같은 결과를 도출하였다. (1) 터널을 통과하는 경우의 도로교통용량은 통과전보다 감소하는 것을 알 수 있으며, 연속되는 터널을 통과하는 경우 감소량은 이보다 큰 것으로 나타났다. (2) 터널보정계수$(f_{tu})$를 도출한 결과 하나의 터널을 통과하는 경우의 터널보정계수$(f_{tu1})$는 0.95, 연속되는 터널을 통과하는 경우의 터널보정 계수$(f_{tu2})$는 0.90으로 산정되었다.

• Journal of Korean Society of Transportation
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• v.35 no.3
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• pp.220-233
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• 2017

Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.295-297
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• 2007

교통 관련 검지기 시스템에 의해 수집된 교통량, 점유율, 속도와 같은 교통 정보 데이터는 품질평가, 오류판단, 결측보정의 자료처리를 거치게 되며 이러한 전처리 후 다양한 목적에 의해 연구자들에게 활용된다. 신속하고 정확한 자료처리와 보다 편리하고 효과적인 웹 UI 의 제공은 매우 중요하다. 본 논문에서는 품질평가, 오류판단, 결측보정에 해당하는 세 단계의 자료처리 알고리즘을 개발하고 사용자에게 자료처리의 과정을 제공하는 웹 UI 시스템을 구현한다.