• Journal of Navigation and Port Research
• /
• v.42 no.6
• /
• pp.453-458
• /
• 2018

The analysis of maritime traffic refers to the processes that are used to analyze the environmental characteristics of the target area and, based on this analysis, predict the traffic pattern of the vessels. In recent years, maritime traffic analysis has become significant with increase maritime traffic volume and expansion of VTS coverage area. In addition, maritime traffic analysis is also applicable in the safety assessment of port facilities and the VTS (Vessel Traffic Service). In this paper, we propose a method to analyze the vessels' traffic pattern by using the heat map and the centroid method. This method is efficient for the analysis of the vessel trajectory data where spatial characteristics change with time. In the experiments, the traffic density and centroid by time have were analyzed. Trajectory data collected at Mokpo harbor was adopted. Finally, we reviewed the experimental results to verify the feasibility of the proposed method as a maritime traffic analysis method.

• International Journal of Highway Engineering
• /
• v.17 no.6
• /
• pp.75-83
• /
• 2015

PURPOSES : This study deals with the traffic accidents classified by the traffic analysis zone. The purpose is to develop the accident density models by using zonal traffic and socioeconomic data. METHODS : The traffic accident density models are developed through multiple linear regression analysis. In this study, three multiple linear models were developed. The dependent variable was traffic accident density, which is a measure of the relative distribution of traffic accidents. The independent variables were various traffic and socioeconomic variables. CONCLUSIONS : Three traffic accident density models were developed, and all models were statistically significant. Road length, trip production volume, intersections, van ratio, and number of vehicles per person in the transportation-based model were analyzed to be positive to the accident. Residential and commercial area ratio and transportation vulnerability ratio obtained using the socioeconomic-based model were found to affect the accident. The major arterial road ratio, trip production volume, intersection, van ratio, commercial ratio, and number of companies in the integrated model were also found to be related to the accident.

• ETRI Journal
• /
• v.26 no.3
• /
• pp.203-217
• /
• 2004

This paper presents a method and architecture to analyze streaming media and multimedia conferencing traffic. Our method is based on detecting the transport protocol and port numbers that are dynamically assigned during the setup between communicating parties. We then apply such information to analyze traffic generated by the most popular streaming media and multimedia conferencing applications, namely, Windows Media, Real Networks, QuickTime, SIP and H.323. We also describe a prototype implementation of a traffic monitoring and analysis system that uses our method and architecture.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.65-80
• /
• 2023

In this study, a classification analysis was performed based on the type of traffic situation. The purpose was to derive the major variable factors that could represent the traffic situation. The TTI(Travel Time Index) was used as a criterion for determining traffic conditions, and analysis was performed using data generally detected by the Vehicle Detecting System(VDS). First, the major factors influencing the traffic situation were selected through factor analysis, and traffic conditions were clustered through a cluster analysis of the major factors. After that, variance analysis for each cluster was performed based on the TTI, and similar clusters were merged to categorize the type of traffic situation. The analysis derived, the maximum queue length and occupancy as major factors that could represent the traffic situation. Through this study, it is expected that efficient management of traffic congestion would be possible by just concentrating on the main variable factors that affect the traffic situation.

• Proceedings of the KSR Conference
• /
• 2010.06a
• /
• pp.769-774
• /
• 2010

KTX Introduced in korea have occurred enhanced services and reduced regional travel time. "Induced traffic" is defined in the traffic demand generated in new project. 'Induced traffic' compared to the Diversion Demand Survey and research on ways to quantify the situation, insufficient analysis of constant and long-term observations are needed to estimate the changes in demand. In this study, Induced traffic effects due to the opening of KTX for analysis survey to passengers by Railway and the scale factor induced traffic review.

• Journal of Korean Society of Transportation
• /
• v.6 no.1
• /
• pp.17-31
• /
• 1988

In this research, the behavior of weaving traffic is studied in terms of lane-changing behavior and gap acceptance characteristics. General trends in lane-changing behavior and gap acceptance characteristics are investigated by analyzing descriptive statistics and the factors affecting weaving behavior are determined by means of the multiple linear regression analysis. The results of analysis show that the behavior of weaving traffic is generally similar to that in a basic freeway section and an on- or of- ramp section. Traffic density and speed appear to be better parameters than traffic volume for explaining the behavior of weaving traffic. For the same purpose, using the traffic conditions of the origin and the destination lanes are found to be more effective than using the average traffic conditions of the freeway. A detailed analysis of the gap acceptance characteristics of late merging vehicles shows that there is no significant difference between the size of gaps accepted by late merging vehicles and that accepted by early merging vehicles.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.45-53
• /
• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.13
• /
• pp.5229-5232
• /
• 2014

Background: While many studies have concluded that local traffic density is positively associated with childhood leukemia, the results are inconsistent. We therefore performed a meta-analysis to assess the relationship between traffic density and the risk of childhood leukemia. Methods: A systematic literature review was carried out using PubMed, EMBASE, and the Cochrane Library from January 1979 to December 2013. We selected and assessed journal articles evaluating the relationship between local traffic density and the risk of leukemia in children. The analysis was carried out using STATA version 12.0. Results: A total of 11 articles, including 12 estimates of effect, were included in our meta-analysis. The summary effect size from the random-effects model, expressed as an odds ratio, was 1.03 (95% CI: 0.98-1.09, p=0.002). No significant association between traffic density and the risk of childhood leukemia was found. Similar conclusions were found on subgroup analysis. Conclusions: The results of our meta-analysis suggested no association between traffic density and the risk of childhood leukemia. This implies that living in close proximity to roads with heavy traffic may not increase the risk of childhood leukemia. However, further high-quality prospective trials are needed to support these results.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.9 no.6
• /
• pp.63-82
• /
• 2010

In spite of continuous road construction, traffic congestion has been worsening by radical vehicle's increase and development of surroundings near expressway. Thus, the necessity of traffic management and the needs of provision of traffic information to drivers are raised. In order to solve traffic problems, such as traffic congestion, search for optimal congestion management technique and evaluation of the effect of optimal solution should be examined prior to practice of optimal alternative. However, existing traffic analysis model and simulation programs as tools to search and evaluate optimal alternative are not sufficient to reflect traffic flow characteristics, domestic road and traffic conditions and to link up to Freeway Traffic Management Systems (FTMS). Hence, to use existing traffic analysis and simulation tools are followed by hard work to need a lot of time and cost. Therefore, in this research, Expressway TRaffic Analysis Model (ExTRAM) based on Freeway Traffic Management Systems (FTMS) was developed to apply it into congestion management easily.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.5
• /
• pp.253-263
• /
• 2021

Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.