• 제목/요약/키워드: Traffic Flow Management

검색결과 284건 처리시간 0.023초

항공교통관제사의 항공기 합류순서결정에 대한 확률적 예측모형 개발 (Probabilistic Model for Air Traffic Controller Sequencing Strategy)

  • 김민지;홍성권;이금진
    • 한국항공운항학회지
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    • 제22권3호
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    • pp.8-14
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    • 2014
  • Arrival management is a tool which provides efficient flow of traffic and reduces ATC workload by determining aircraft's sequence and schedules while they are in cruise phase. As a decision support tool, arrival management should advise on air traffic control service based on the understanding of human factor of its user, air traffic controller. This paper proposed a prediction model for air traffic controller sequencing strategy by analyzing the historical trajectory data. Statistical analysis is used to find how air traffic controller decides the sequence of aircraft based on the speed difference and the airspace entering time difference of aircraft. Logistic regression was applied for the proposed model and its performance was demonstrated through the comparison of the real operational data.

Stochastic Traffic Congestion Evaluation of Korean Highway Traffic Information System with Structural Changes

  • Lee, Yongwoong;Jeon, Saebom;Park, Yousung
    • Asia pacific journal of information systems
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    • 제26권3호
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    • pp.427-448
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    • 2016
  • The stochastic phenomena of traffic network condition, such as traffic speed and density, are affected not only by exogenous traffic control but also by endogenous changes in service time during congestion. In this paper, we propose a mixed M/G/1 queuing model by introducing a condition-varying parameter of traffic congestion to reflect structural changes in the traffic network. We also develop congestion indices to evaluate network efficiency in terms of traffic flow and economic cost in traffic operating system using structure-changing queuing model, and perform scenario analysis according to various traffic network improvement policies. Empirical analysis using Korean highway traffic operating system shows that our suggested model better captures structural changes in the traffic queue. The scenario analysis also shows that occasional reversible lane operation during peak times can be more efficient and feasible than regular lane extension in Korea.

교통망에서 다차종 통행을 고려하는 통행배정모형 수립 (A Traffic Assignment Model in Multiclass Transportation Networks)

  • 박구현
    • 한국경영과학회지
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    • 제32권3호
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    • pp.63-80
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    • 2007
  • This study is a generalization of 'stable dynamics' recently suggested by Nesterov and de Palma[29]. Stable dynamics is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with user equilibrium model that is common in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on the congestion. Therefore it is expected to be an useful analysis tool for transportation planners. An equilibrium in stable dynamics needs only maximum flow in each arc and Wardrop[33] Principle. In this study, we generalize the stable dynamics into the model with multiple traffic classes. We classify the traffic into the types of vehicle such as cars, buses and trucks. Driving behaviors classified by age, sex and income-level can also be classes. We develop an equilibrium with multiple traffic classes. We can find the equilibrium by solving the well-known network problem, multicommodity minimum cost network flow problem.

유비쿼터스 교통환경을 위한 연속류 정체예방관리 알고리즘 (Preventive Congestion Management Algorithm for Ubiquitous Freeway System)

  • 박은미
    • 대한교통학회지
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    • 제27권3호
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    • pp.161-168
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    • 2009
  • 유비쿼터스 교통환경에서는 개별차량의 위치, 속도 등 미세한 데이터 수집이 가능하며, V2V (Vehicle-to-Vehicle), V2I(Vehicle-to-Infra) 양방통신이 가능해 짐에 따라 개별차량 혹은 차량군 단위의 미세 제어가 가능해 진다. 이와 같이 기존 ITS 환경과 차별화되는 유비쿼터스 교통환경에 합당한 새로운 교통관리 개념을 정립하는 것과 이러한 개념을 실현할 알고리즘 개발도 필요하다. 이에 본 논문에서는, 교통류 안정성 유지를 통하여 사고발생 잠재력을 최소화시키고 생산성 저하를 방지하는 예방차원의 u-연속류 정체예방관리 서비스를 정의하고 알고리즘을 개발하였다. 이러한 u-연속류 정체예방관리 알고리즘에는 다음과 같은 요소기술 개발이 포함된다. 첫째, 유비쿼터스 교통센터 네트워크에서 수집된 개별차량 데이터를 처리하여, 3차원의 속도/교통량/밀도 프로파일을 구성하는 기술. 둘째, 차량군과 충격파 프로파일을 추출하는 기술. 셋째, 위의 데이터 처리를 통하여 교통류 안정성을 판단하고 교통상황을 구분하는 기술. 넷째, 교통 상황별 적정속도 산정 기술. 다섯째, V2V, V2I 통신환경을 이용한 개별차량 혹은 차량군 단위 적정속도 제공 기술. 기존의 ITS 환경의 사후관리와 비교할 때, 본 연구에서 제안하는 정체예방관리는, 예방적 차원의 사전관리라는 점에서 진일보한 교통류 관리이다. 향후 유비쿼터스 교통 환경을 모사할 수 있는 시뮬레이션 모형 개발이 필요하며, 테스트 베드를 구축하여 현장실험을 시행하고 알고리즘에서 요구되는 문턱치를 결정하는 것도 필요하다.

Energy Efficient Cell Management by Flow Scheduling in Ultra Dense Networks

  • Sun, Guolin;Addo, Prince Clement;Wang, Guohui;Liu, Guisong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권9호
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    • pp.4108-4122
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    • 2016
  • To address challenges of an unprecedented growth in mobile data traffic, the ultra-dense network deployment is a cost efficient solution to off-load the traffic over other small cells. However, the real traffic is often much lower than the peak-hour traffic and certain small cells are superfluous, which will not only introduce extra energy consumption, but also impose extra interference onto the radio environment. In this paper, an elastic energy efficient cell management scheme is proposed based on flow scheduling among multi-layer ultra-dense cells by a SDN controller. A significant power saving was achieved by a cell-level energy manager. The scheme is elastic for energy saving, adaptive to the dynamic traffic distribution in the office or campus environment. In the end, the performance is evaluated and demonstrated. The results show substantial improvements over the conventional method in terms of the number of active BSs, the handover times, and the switches of BSs.

효율적인 항공교통흐름을 위한 항로 연산 알고리즘 연구 (A Study On Route Calculation Algorithm For Effective Air Traffic Flow Management)

  • 김용균;조윤현;윤진원;박동화;최상방;박효달
    • 한국항행학회논문지
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    • 제14권2호
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    • pp.161-169
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    • 2010
  • 최근 항공교통량의 증가에 따라 보다 효율적인 항공교통흐름제어가 요구되고 있다. 이에 본 논문에서는 효율적인 항공관제를 위하여 항공기의 흐름을 유연하게 하기 위한 알고리즘 기법을 연구하였다. 항공교통 환경은 일반 교통 환경과는 다르게 항공기 기종에 따른 수평 및 수직 분리 간격이 존재한다. 빈센티 공식을 이용하여 항로의 거리를 산출하고 다익스트라 알고리즘을 이용하여 항로의 거리에 교통량을 적용하여 가중치를 생성하고 이를 이용하여 항공기가 연료 및 시간의 낭비를 최소화하는 항로를 선택하도록 하였다. 성능평가 결과 기존의 항로 연산 알고리즘의 단순한 최단항로 산출과는 달리 제안된 알고리즘은 교통량 파악을 통한 최적항로를 선택함으로써 효율적으로 항공교통관제를 할 수 있음을 확인하였다.

우리나라 연안의 해상교통관제시스템 설치를 위한 기초연구 시뮬레이션에 의한 우리나라 연안의 해상교통량 추정 ( Estimation of the Traffic Flow in the Korea Coastal Waterway by Computer Simulation)

  • 구자윤;박양기;이철영
    • 한국항해학회지
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    • 제12권1호
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    • pp.85-112
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    • 1988
  • From the point of view of safety of life and property at sea and the protection of the marine environment, the Vessel Traffic Management System along the Korea coastal waterway is inevitably introduced. But the establishing priority per area must be evaluated under the restricted budget. In this case, the estimated traffic flow has a major effect on priority evaluation. In the former paper , an algorithm was proposed for estimating the trip distribution between each pair of zones such as harbours and straits. This paper aims to formulate a simulation model for estimating the dynamic traffic flow per area in the Korea coastal waterway. The model consists of the algorithm constrined by the statistical movement of ships and the observed data, the regression analysis and the traffic network evaluations. The processed results of traffic flow except fishing vessel are summarized as follows ; 1) In 2000, the traffic congestions per area are estimated, in proportion of ship's number (tonnage), as Busan area 22.3%(44.5%), Yeosu area 19.8%(11.2%), Wando-Jeju area18.1%(6.8%), Mokpo area 14.9%(9.9%), Gunsan area 9.1%(9.3%), Inchon area 8.1%(7.7%), Pohang area 5.5%(8.5%), and Donghae area 2.2%(2.1%). 2) For example in Busan area, the increment of traffic volume per annum is estimated 4, 102 ships (23 million tons) and the traffic flow in 2000 is evaluated 158, 793 ships (687 million tons). 3) consequently, the increment of traffic volume in Busan area is found the largest and followed by Yeosu, Wando-Jeju area. Also, the traffic flow per area in 2000 has the same order.

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교통난 계측 I-초음파용 공간필터법에 의하여- (A Measurement of Traffic Vehicles Flow by the Ultrasonic Spatial Filtering Method)

  • 전승환
    • 한국항해학회지
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    • 제20권2호
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    • pp.51-58
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    • 1996
  • For the smooth flow of traffic vehicles and its effective management, it is necessary to have an exact information on traffic condition, i.e., the volume of traffic, velocity, occupancy and classification of vehicles. In particular, for classification of vehicles, there has been only image processing method using camera, where the method can obtain much information but rather expensive. In this paper, an algorithm for the measurement of velocity and total length of vehicles has been proposed to develop a general traffic management system, which is necessary to discriminate the class of vehicles. In order to realize the proposed algorithm, we have developed an ultrasonic spatial filtering method, which has better performance than that of using the traditional vehicle detector. To have this system to be constructed, we have introduced three sets of ultrasonic devices where each has one transmitter and two receivers which are arranged to obtain the spatial difference of objects. The velocity of vehicles can be measured by analyzing the occurrence time of pulses and their time differences. The total length of vehicles can be given by multiplying velocity with time interval of pulses sequence. To confirm the effectiveness of this measuring system, the experiment by the spatial filtering method using the ultrasonic sensors has been carried out. As the results, it is found that the proposed method can be used as one of measurement tools in the general traffic management system.

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Multivariate Congestion Prediction using Stacked LSTM Autoencoder based Bidirectional LSTM Model

  • Vijayalakshmi, B;Thanga, Ramya S;Ramar, K
    • 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.

A Video Traffic Flow Detection System Based on Machine Vision

  • Wang, Xin-Xin;Zhao, Xiao-Ming;Shen, Yu
    • 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.