PURPOSES : Traffic volume, an important basic data in the field of road traffic, is collected from traffic survey equipment installed at certain locations, which sometimes results in missing traffic volume data and abnormal detection. Therefore, this study presents various missing correction techniques using traffic characteristic analysis to obtain accurate traffic volume statistics. METHODS : The fundamental premise behind the development of a traffic volume correction and prediction model is to set the corrected data as the reference value, and the traffic volume correction and prediction process for the outliers and missing values in the raw data were performed based on the set values. RESULTS : The simulation results confirmed that the algorithm combining seasonal composition, quantile AD, and aggregation techniques showed a detection performance of more than 91% compared with actual values. CONCLUSIONS : Raw data collected due to difficulties faced by traffic survey equipment will result in missing traffic volume data and abnormal detection. If these abnormal data are used without appropriate corrections, it is difficult to accurately predict traffic demand. Therefore, it is necessary to improve the accuracy of demand prediction through characteristic analysis and the correction of missing data or outliers in the traffic data.

PURPOSES : This study analyzes the estimated traffic volumes on roads and railways based on econometrics. METHODS : The accuracy of traffic forecasting was analyzed based on the average difference between predicted and actual values. This study distinguishes itself from existing literature by conducting a comparative analysis categorized by project type. In this study, econometric analyses, including bias and efficiency evaluation, were conducted for 308 projects in Korea. RESULTS : We conducted econometric analysis by dividing the data into project types. This study examines the accuracy of estimates in South Korea's road and railway projects concerning various factors, including project types (mobility-focused or accessibility-focused), implementing agencies, and the performance of preliminary feasibility studies. Notably, it identifies a tendency for overestimation, particularly in railway projects and mobility-focused road projects, such as expressways and national highways, as well as in projects executed by local governments. The mean percentage error (MPE) for the analyzed projects was -46.62%, indicating a significant overestimation bias with resulting inefficiencies. However, our analysis revealed that road projects, particularly those accompanied by preliminary feasibility studies and implemented by the central government, exhibited reduced bias and improved efficiency. The presence or absence of preliminary feasibility studies significantly influenced estimation bias. Interestingly, even when preliminary feasibility studies are conducted, the choice of the implementing agency remains a crucial factor affecting estimation bias. In addition, railway projects continue to demonstrate a notable overestimation bias, warranting further attention. CONCLUSIONS : Considering bias, efficiency, and MPE is advisable when forecasting traffic.

PURPOSES : This study verifies the appropriateness of the observed traffic volume using car navigation traffic volume data. METHODS : In this study, we developed an annual average daily traffic (AADT) estimation model that can verify the total amount of traffic by using navigation traffic volume data. In addition, a method to verify the appropriateness of the observed traffic volume was developed using time-based navigation traffic volume data that can check the characteristics of traffic volume at each point. RESULTS : As a result of the analysis of this study, it was found that 674 of the 697 short-duration survey spots of the freeways were appropriate and that 23 spots needed to be revised. CONCLUSIONS : As a result of the analysis of this study, it was found that there was a strong positive correlation between the observed traffic volume and the car navigation traffic volume. Thus, the appropriateness of the observed traffic was determined by verifying the total amount of observed traffic and the observed traffic volume by time.

PURPOSES : Despite the availability of larger traffic data and more advanced data collection methods, the problem of missing data is yet to be solved. Imputing missing data to ensure data quality and reliability of statistics has always been challenging. Missing data are imputed via several existing methods, such as autoregressive integrated moving average, exponential smoothing, and interpolation. However, these methods are complicated and results in significant errors. METHODS : A deep-learning method was applied in this study to impute traffic volume data of the South Korean national highway. Traffic data were trained using the long short-term memory method, which is a suitable deep-learning method for time series analysis. RESULTS : Three cases were proposed to estimate the traffic volume. In the first case, which represented the general conditions, the mean absolute percentage error (MAPE) was 12.7%. The second estimation case, which was based on the opposite traffic flow, exhibited a MAPE of 17%~18%. The third case, which was estimated using adjacent-section data, had a MAPE of 18.2%. CONCLUSIONS : Deep learning may be a suitable alternative data imputation method based on the limited site and data. However, its application depends on the specific situation. Furthermore, deep-learning models can be improved using an ensemble method, batch-size, or through model-structure optimization.

지난 22년 동안의 선박 통항자료와 2015년부터 2017년까지 3년 동안 매년 72시간씩 실시간 선박 통항량 조사를 통해 여수광양항의 해상교통량의 장기변동과 출입항로에 대한 통항특성을 분석하였다. 2017년도 기준으로, 여수광양항의 선박 통항척수는 약 66,000척이며, 선복 량은 약 804,564천톤으로 1996년도 189,906천톤에 비해 400 % 이상 증가하였고 위험화물 물동량은 140,000천톤으로 1996년에 비해 250 % 이상 증가한 것으로 나타났다. 실시간 선박 통항량 조사결과, 1일 평균 통항 선박은 357척이며 통항로 이용율은 낙포해역이 28.1 %, 특정해역이 43.8 %, 연안통항로와 돌산연안 및 금오도 수역이 6.8 %로 동일하였다. 다수의 항로가 만나는 낙포해역은 선박간의 병항 및 교차항행이 가장 빈번했으며, 특정해역도 주변의 연안통항로에서 소형 작업선들이 다수 진출입하여 대형 선박과 교차되는 경우가 자주 발생하였다. 화물선박 의 묘박지 투묘 대기율은 약 24 % 정도였으며, 케미컬선, 유조선 등의 위험화물 선박의 야간 통항율은 약 20 %에 달하였다. 여수광양항의 선 박 통항량은 매년 증가하지만 선박 통항로는 과거와 큰 차이가 없기에 사고의 위험이 상존한다고 볼 수 있다. 따라서 다수의 항로가 중첩되어 통항 선박간의 사고 위험이 높은 제1항로 ~ 제4항로의 준설 및 항로 확장, 항로 부근 암초 제거, 항로표지 보강 등 항로 여건을 우선적으로 개선할 필요가 있다. 또한 위험성이 높은 항만의 진출입 시간과 위험화물 선박의 통항시간을 일부 제한할 수 있도록 항행규칙을 개정할 필요가 있으며, 연안통항로를 이용하는 소형 선박들의 통항관리를 적극적으로 시행할 수 있도록 VTS체계의 고도화가 요구된다.

PURPOSES : The purpose of this study is to develop a service volume for signal metering on roundabouts to increase applicability of roundabout in Korea. METHODS: To develop the service volume for signal metering on roundabouts, traffic simulation studies were conducted using VISSIM software for various scenarios based on traffic volumes as approaches and location of detectors on controlling approach lane. Typically, the Vehicle Actuated Programming module in VISSIM was applied for analyzing more realistic traffic signal control conditions. RESULTS: As the left-turning volume is increased, the delay reduction rates were increased. And the case of 40 meter distance of a detector and 20 seconds red signal phase made better results. CONCLUSIONS: The signal metering on roundabout should be applied carefully because it is possible to lose roundabout strengthen in traffic operation aspect. The service volume for signal metering on roundabouts that suggested from this study is useful to decide the application of signal metering on roundabout.