• Title/Summary/Keyword: Traffic Flow Pattern

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Development of Saturation Flow Rate Estimation Models Considering Workzone in the Vicinity of Signalized Intersections (도시부 신호교차로 인근 도로점용공사를 고려한 포화교통류율 산정모형 개발에 관한 연구)

  • Eo, Hyo-Gyeong;Sin, Chi-Hyeon
    • Journal of Korean Society of Transportation
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    • v.28 no.6
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    • pp.109-120
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    • 2010
  • This study aims to develop mathematical models for estimating saturation flow rates at the stop line of signalized intersection due to Workzones in the vicinity, since the saturation flow rate is the most critical parameter in capacity analysis for signalized intersections. It was found by reference review that saturation flow rates are sensitively influenced by the location of Workzone, the number of lanes, cycle length and effective green time. Extensive microscopic simulation runs were also performed and compared to the those of mathematical models for model verification. Mathematical models were developed based on traffic flow theory and dualizing them by the location of workzones. And then each result produced by changing important parameter values was carefully examined and analyzed. Small but consistent differences in saturation flow rate values between mathematical models and simulations exist. However, the pattern of changes in saturation flow rates depending on each variable was similar.

Backward Moving Shockwave Speed Measurement in Traffic Images (교통 영상에서의 Backward Moving 충격파 속도 측정)

  • 권영탁;소영성
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.3
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    • pp.6-13
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    • 2002
  • In this paper, we propose an image processing based method to measure red-time and green-time backward moving shockwave speed automatically at signalized intersections. Shockwave means the discontinuous boundary line between different vehicle traffic flows, and its moving speed is called shockwave speed which is obtain from the slope of boundary line. In this paper, we compose distance-time diagram for measuring shockwave speed automatically. By global vehicle tracking, we draw all of the vehicle moving path on distance-time diagram. We analyze the slope change pattern of curved moving path line, and compute red-time and green-time backward moving shockwave speed. We obtain the measurement result of shockwave speed, when applying above mentioned proposed method to experiment at signalized intersections, Once we can measure the shockwave speed, we could apply the result to highway ramp metering and automatic signal control at intersections effectively since we know the situation of frontal congestion easily.

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Development of Method to Define Influence Area using Travel Time on the Feasibility Study (도로사업 예비 타당성조사에서 통행시간을 이용한 영향권 설정기법의 개발)

  • Kim, Kang-Soo;Oh, Dong-Kyu;Chung, Sung-Bong
    • Journal of Korean Society of Transportation
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    • v.23 no.8 s.86
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    • pp.139-145
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    • 2005
  • `Influence Area` means the area that the traffic flow pattern of which is changed remarkably after the construction of highway facilities. The Influence area would be a significant criteria for demand forecasting and economic analysis. However existing methods for defining influence area such as O/D method, traffic volume variation method and rate of traffic volume variation method have no standard criteria. In this paper, some problems which existing methods have are analyzed and a new method travel time method - is introduced. Influence area can be induced as the area where the vehicles reach from starting traffic zone to ending zone to which 95 percentile vehicles want to travel. In addition, the value of standard criteria for defining influence ayes are induced via this method.

An Analysis on the Operational Status of the Korea Coastal Cargo Vessel (한국연안화물선운실태의 분석)

  • 우창기;이철영
    • Journal of the Korean Institute of Navigation
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    • v.11 no.1
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    • pp.1-38
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    • 1987
  • The amount of cargoes by cargo vessels has increased tremendously during the last decade due to the great growth of korea economy. But in spite of this trend, there is rarely the substantial analyzed on the operational status of coastal shipping. In this paper, the characteristics of seaborne cargo and traffic flow of coastal shipping surveyed in detail through the statistical and the origintain and destination (O.D) analysis. Also, the basic ship's tonnage of coastal shipping representing the minimum tonnage which is capable of carrying the given seaborne cargo is suggested through the computer simulation using the data of 1985 year. The results are as follows; 1) the about 80% of total coastal traffic volume is going in/out to the port of Incheon, Busan, Pohang, Samil, Bukpyung, Mukho, Samchuk, and Jeju. 2) The main cargo items such as oil, iron material, cement, anthracite grain, fertilizer, other ore are reached to the about 70% of total amount of coastal trade. 3) ship's tonnage going in/out to the port of Bukpyiung, Busan, Pohang is increasing linearly year by year, and the amount of oil, iron material, cement, anthracite, grain, fertilizer, other ore are also increasing in linear pattern. 4) As a result of simulation, the optimum (basic) ship's tonnage.

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A Study on Improving Subway Crowding Based on Smart Card Data : a Focus on Early Bird Policy Alternative (교통카드 자료를 활용한 지하철 혼잡도 개선 연구 : Early Bird 정책대안을 중심으로)

  • Lee, Sang Jun;Shin, Sung Il
    • Journal of Information Technology Services
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    • v.19 no.2
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    • pp.125-138
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    • 2020
  • Currently, subway crowding is estimated by observing a specific point at specific hours once or twice every 1 or 2 years. Given the extensive subway network in Seoul Metropolitan Area covering 588 stations, 11 lines and 80 transfer stations as of 2017, implementing crowding mitigation policy may have its limitations due to data uncertainty. A proposal has recently been made to effectively use smart card data, which generates big data on the overall subway traffic related to an estimated 8 million passengers per day. To mitigate subway crowding, this study proposes two viable options based on data related to smart card used in Seoul Metropolitan Area. One is to create a subway passenger pattern model to accurately estimate subway crowding, while the other is to prove effectiveness of early bird policy to distribute subway demand that is concentrated at certain stations and certain time. A subway passenger pattern model was created to estimate the passenger routes based on subway terminal ID at the entrance and exit and data by hours. To that end, we propose assigning passengers at the routes similar to the shortest routes based on an assumption that passengers choose the fastest routes. In the model, passenger flow is simulated every minute, and subway crowding level by station and line at every hour is analyzed while station usage pattern is identified by depending on passenger paths. For early bird policy, highly crowded stations will be categorized based on congestion level extracted from subway passenger pattern model and viability of a policy which transfers certain traveling demands to early commuting hours in those stations will be reviewed. In particular, review will be conducted on the impact of policy implemented at certain stations on other stations and lines from subway network as a whole. Lastly, we proposed that smart card based subway passenger pattern model established through this study used in decision making process to ensure effective implementation of public transport policy.

Development of a Daily Pattern Clustering Algorithm using Historical Profiles (과거이력자료를 활용한 요일별 패턴분류 알고리즘 개발)

  • Cho, Jun-Han;Kim, Bo-Sung;Kim, Seong-Ho;Kang, Weon-Eui
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.10 no.4
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    • pp.11-23
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    • 2011
  • The objective of this paper is to develop a daily pattern clustering algorithm using historical traffic data that can reliably detect under various traffic flow conditions in urban streets. The developed algorithm in this paper is categorized into two major parts, that is to say a macroscopic and a microscopic points of view. First of all, a macroscopic analysis process deduces a daily peak/non-peak hour and emphasis analysis time zones based on the speed time-series. A microscopic analysis process clusters a daily pattern compared with a similarity between individuals or between individual and group. The name of the developed algorithm in microscopic analysis process is called "Two-step speed clustering (TSC) algorithm". TSC algorithm improves the accuracy of a daily pattern clustering based on the time-series speed variation data. The experiments of the algorithm have been conducted with point detector data, installed at a Ansan city, and verified through comparison with a clustering techniques using SPSS. Our efforts in this study are expected to contribute to developing pattern-based information processing, operations management of daily recurrent congestion, improvement of daily signal optimization based on TOD plans.

A Service Model Development Plan for Countering Denial of Service Attacks based on Artificial Intelligence Technology (인공지능 기술기반의 서비스거부공격 대응 위한 서비스 모델 개발 방안)

  • Kim, Dong-Maeong;Jo, In-June
    • The Journal of the Korea Contents Association
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    • v.21 no.2
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    • pp.587-593
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    • 2021
  • In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

Bus Platoon Separation and Intersection Delay Analysis (버스군(群) 분리특성(分離特性)과 교차로(交叉路) 지체분석(遲滯分析))

  • Sul, Jae Hoon;Park, Chang Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.8 no.1
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    • pp.25-32
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    • 1988
  • Vehicle platoons starting a stopline are dispersed while travelling along the street and the delay at the next intersection depends on the arrival pattern of dispersed traffic flow. In this paper, the platoon dispersion charactiristics of our country, especially the time gap between passenger cars and buses caused by the dwell time at bus stops, were investigated through travel time surveys. Based on the survey results, on improved analysis method of intersection delay is proposed.

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Interior Project of Daejeon DS Skin Clinic (대전 DS피부과 인테리어 계획)

  • Kim, Suk-Young
    • Proceedings of the Korean Institute of Interior Design Conference
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    • 2006.11a
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    • pp.179-182
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    • 2006
  • This project is for a Branch clinic of DS Skin Clinic who currently runs two other skin clinics in Daejeon Province. The major consideration of the project is to provide the high quality space appropriate for the unique medical services compared to any other skin clinics. The concept of the design is 'spaciousness of the past' and actual design elements used in this space is 'Frame', 'Smooth Traffic Pattern', 'Eye Flow', 'Faded looking finishes and colors of material' Overall space is divided into 2 areas, which are Dermatology Department providing medical service and Skin Clinic Department providing skin and body care. Those 2 areas are connected to each other through a circular reception area for administration, storage, and public area.

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Video Road Vehicle Detection and Tracking based on OpenCV

  • Hou, Wei;Wu, Zhenzhen;Jung, Hoekyung
    • Journal of information and communication convergence engineering
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    • v.20 no.3
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    • pp.226-233
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    • 2022
  • Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.