• 한국도로학회논문집
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• 제15권1호
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• pp.163-169
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• 2013

PURPOSES: The urban traffic problems can be defined as general problems for smooth traffic flow including maintenance of mass transportation system according to suddenly increased population, traffic regulations for vehicles and pollution problem. As a method for solving traffic jams, one of the traffic problems of late, interest in Intelligent Traffic System(ITS) is increasing sharply, which is a system managing traffic demand by providing passers with information on traffic state of path and road conditions before they pass the road through ATIS, a field of ITS. METHODS: Variable message signs(VMS) is used on the roads as a method for providing information to promote smooth traffic flow and safety and prevent traffic accidents in advance by providing drivers with various information while driving. RESULTS: Recently, as ITS industry has been vitalized and technical factors of VMS have developed, various kinds of information is provided but the effect of VMS has not been maximized due to its limited type. CONCLUSIONS: Therefore, this study intends to provide methods for effective information transfer by analyzing driver's visual behavior characteristics for VMS and presenting a basis for maximizing VMS effect after considering read by expression type.

• 한국도로학회논문집
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• 제17권4호
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• pp.107-115
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• 2015

PURPOSES: This study analyzes the characteristics of traffic flow on freeway sections under daytime and nighttime conditions to improve traffic safety, and suggests a method to estimate an accurate freeway capacity value that reflects these characteristics. METHODS : The trends and differences in capacity were investigated using comprehensive field data collected under both daytime and nighttime conditions on freeway sections with designated speeds of 80, 100, and 120 kph. RESULTS : The capacity values under nighttime driving conditions were reduced by 3.3%, 6.9%, and 8.8% at 80, 100, and 120 kph, respectively. Several nighttime adjustment factors were deduced for each designated speed category from the analysis results. CONCLUSIONS : It is expected that more accurate capacity values can be estimated for freeway sections under nighttime conditions by applying the resulting adjustment factors. In addition, traffic safety will be improved through the increased efficiency of traffic management on these freeway sections.

• 한국ITS학회 논문지
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• 제4권1호
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• pp.43-56
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• 2005

본 연구는 점유율, 교통량, 속도 등의 실시간 교통자료의 시계열 분석, 교통기초도 상 실측자료의 통계적 모형화와 교통류의 다영역 구분에 의한 교통정체의 전개 양상을 규명하였다. 천안-논산고속도로의 교통사고와 행사로 인한 교통정체 시의 검지기 자료를 바탕으로 시계열 분석을 수행한 결과 교통사고와 같이 급격히 도로 콩량이 감소하는 경우 사고 직후 점유율의 변화로부터 용이하게 추정할 수 있었다. 행사와 같은 교통량 증가로 인한 교통정체의 경우 점유율과 평균속도의 변화 폭이 완만하며, 충격파의 형태가 다양하여 단순한 교통지표들의 시계열적 분석에 의한 검지의 신속성과 정확성에는 어려움이 있는 것으로 나타났다. 실측자료의 통계적 모형화에 있어서 안정교통류일 경우 점유율과 교통량 관계는 1차 선형식으로 매우 높은 신뢰도로 설명되었다. 그러나 속도와 점유율간의 관계에 있어서는 운전자들의 희망속도에 대한 넓은 폭원으로 인하여 나타나는 군집형태가 통계적 모형으로 표현되기에는 어려운 것으로 나타났다 그러나 이 경우 점유율 6-8$\%$대를 중심으로 속도가 급격히 떨어지는 현상이 발생하였다. 불안정 교통류 상황의 경우 교통정체의 형성과 해소과정이 각기 하나의 영역 내에서 분석됨에 따라 전반적으로 통계적 모형의 적용이 어려운 것으로 나타났다. 안정과 불안정 2영역 구분에 의한 교통정체 형성과 해소과정의 해석이 어려운 점을 감안하여 다영역 구분에 의한 교통류를 시계열에 의하여 분석한 결과 사고시의 교통류는 바로 정지단계(stopped flow)로 전이되며 점유율이 급격히 증가하였으며, 교통류가 stooped flow에서 free flow로 회복될 때 급격히 증가된 점유율이 점진적으로 감소하면서 교통량이 증가하는 추세를 나타냈다. 교통혼잡시의 교통류는 "impeded free flow" 상황에서 "congested flow" 상황을 거쳐 "jammed flow" 상황으로 전개되는 등 사고에 의한 정체 형성 및 해소과정보다 매우 복잡하며, 동일한 점유율에 대하여 교통상태별로 교통량의 차이가 큰 현상이 명확하게 발생하였다. 본 연구는 교통류 분석 시 다영역 구분의 필요성을 제시하였으며, 향후 개별 교통영역에 대한 정량적 구분 및 모형화가 이루어져야 할 것을 제기하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1218-1230
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• 2019

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

• 대한토목학회논문집
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• 제30권2D호
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• pp.105-111
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• 2010

주행속도는 고속도로 설계와 운영에 있어 주요한 요소 중 하나이다. 거시적으로 자유교통류 속도(FFS)를 분석한 몇 몇 연구가 보고되고 있으나, 표본수가 적고 교통량과 일중 시간대의 영향을 고려하지 않았다. 본 연구는 FFS의 특성을 분석하기 위해 방대한 양의 표본을 이용하여 자유교통류 상태에서 교통량 수준별 일중 시간대별에 따른 FFS의 분포와 Percentile속도를 미시적으로 분석하였다. 분석결과, 속도분포는 교통량(1-5대/30초)과 일중 시간대(0-5, 6-8, 9-11, 12-19, 20-23)에 따라 변화하였으며 다른 행태를 보였다. 아침, 저녁, 심야 시간대의 V85(85th Percentile 속도)는 교통량이 증가함에 따라 감소하였지만, 오전과 오후 시간대의 V85는 큰 변화를 보이지 않았다. 따라서 시간대에 따른 V85는 교통량이 증가함에 따라 급격하게 변화하였다.

• 대한교통학회지
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• 제14권2호
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• pp.7-29
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• 1996

Traffic flow characteristics is analysed on eight multi-lane roads which are unsignalized in urban areas. Data of traffic flow rates by classification and average speed were gathered every ten minutes interval for twenty-four hours. Machine (NC-90A) was used to acquire the field data. The major purpose of this study is to build up speed-density models on urban arterial roads. Five different kinds of models were tested. Those models are Greenshields' model, Greenberg's model, modified Greenberg's model, Underwood's model and Drake's model. The modified Greenberg's model fits best at six points and the Greenshield's model fits best two points out of eight points. The breakpoint(Kb) of modified Greenberg's model is between 10 and 32 pcphpl. Capacity drawn from speed-volume relationships were appeared to be arround 2,000 and 2,200 pcphpl at the Hannam Bridge and the Hannam Overpass and 1,100 and 1,700 pcphpl at Namsan Tunnel(No1) and the beginning point of Gyeong-Bu Expressway.

• 한국항만학회지
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• 제13권1호
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• pp.113-122
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• 1999

Congestion and traffic accidents occur on the merge and diverge sections in the interchange of the freeway. Studies have been conducted to reduce the traffic delay and accidents on the merge section in the freeway since 1960s. but a study was not conducted to estimate the speed variation on the merge section construct models estimated for the speed variation and suggest the appropriate measures. The purpose of this study was to identify the traffic flow characteristics on the merge section in the freeway construct the models estimated for the speed variation on the merge section in the freeway and finally establish the appropriate measure for reduction of traffic delay and accidents on the merge section in the freeway. The following results were obtained: I) Speed variations in the urban freeway appeared to be about 3.2mph, 6.5mph and 7.4mph based on the morning peak period, afternoon peak period and 24-hours period but those in the suburban freeway appeared to be about 8.0mph, 11.1mph and 10.1mph based on the same periods respectively. So different speed reduction signs need be installed to reduce delay and accidents on the merge section in the freeway based on the areas and periods as the freeway traffic management system(FTMS). ii) These models estimated for speed variation need to be studied with the changeable message sign(CMS) technique based on the real-time data so that the traffic flow could be maximized and the traffic delay and accidents be on the merge section in the freeway as more efficient freeway traffic management system(FTMS) in the near future.

• 한국멀티미디어학회논문지
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• 제18권2호
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• pp.189-198
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• 2015

Despite the fact that traffic engineering techniques have been comprehensively utilized in the past to enhance the performance of communication networks, the distinctive characteristics of Software Defined Networking (SDN) demand new traffic engineering techniques for better traffic control and management. Considering the behavior of traffic, large flows normally carry out transfers of large blocks of data and are naturally packet latency insensitive. However, small flows are often latency-sensitive. Without intelligent traffic engineering, these small flows may be blocked in the same queue behind megabytes of file transfer traffic. So it is very important to identify large flows for different applications. In the scope of this paper, we present an approach to detect large flows in real-time without even a short delay. After the detection of large flows, the next problem is how to control these large flows effectively and prevent network jam. In order to address this issue, we propose an approach in which when the controller is enabled, the large flow is mitigated the moment it hits the predefined threshold value in the control application. This real-time detection, marking, and controlling of large flows will assure an optimize usage of an overall network.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2005년도 추계학술대회 논문집
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• pp.111-116
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• 2005

2006년 영일만 신항이 개장할 경우 포항항 진입 수역은 현재보다도 선박 통항량이 증가하고 중대형 선박들의 입출항이 가속화될 것으로 사료된다. 그러나 포항항 일부 진입 수역에는 여전히 항행 위험 요소가 존재하고 있고, 호미곶 인근 해역에서의 무질서한 항행 및 교통 폭주 등 포항항 진입 항로에 대한 통항 안전성을 위한 교통 환경 개선이 절실히 요구되고 있다. 본 연구에서는 포항항 진입 수역에 대한 교통 현황 실태와 통항 선박의 행동 특성을 고찰하기 위하여 포항항 진입 수역을 대상으로 특정 기간 동안 해상교통조사를 전용 소프트웨어를 이용하여 실시하였다. 또한 해상교통조사 결과를 선종별 및 톤수별로 통계 처리하고 통항 선박의 항적 분포 등을 토대로 통항 선박의 주요 통항로와 통항 특성 등을 고찰하였으며, 향후 포항항 진입 수역의 항로지정에 활용하고자 한다.