• Title/Summary/Keyword: 교통패턴

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Analysis of Traffic flow on the Lane Closure due to Road Construction (도로공사로 인한 차선폐쇄시 교통류 특성에 관한 연구)

  • 오주삼
    • Proceedings of the KOR-KST Conference
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    • 1998.10a
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    • pp.116-125
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    • 1998
  • 도로공사로 인해 차선의 일부가 폐쇄된 경우에 이용하는 차선에 따라서 운전자의 통행패턴은 달라진다. 공사구간이 없는 경우 운전자의 차선변경은 제한적이나마 각 차선의 밀도에 의해서 좌우되는 것으로 나타났다. 또한 차선폐쇄지점 전방에서는 차선변경할 확률은 폐쇄지점까지의 남은 거리에 따라서 음지수함수를 따르는 것으로 확인되었다. 또한 논문에서 공사구간에서의 차선변경행태와 교통량, 밀도, 속도를 산정하였으며, 공사로 인한 차선별 지체시간을 산정하였다.

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Traffic Sign Recognition Using Color Information and Neural Network with Multi-layer Perceptron (컬러정보와 다층퍼셉트론 신경망을 이용한 교통표지판 인식)

  • Bang, Gul-Won;Kang, Dea-Yook;Kim, Byung-Ki;Cho, Wan-Hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2007.05a
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    • pp.305-308
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    • 2007
  • 본 논문은 교통표지판을 자동으로 인식하는 방법에 관한 연구로 기존의 교통표지판 인식시스템에서는 인식하는데 걸리는 시간이 길고 잡음환경에서 인식률이 저하되며 변경된 교통표지판은 인식하지 못하는 문제점이 있다. 본 논문에서는 이와 같은 문제점을 해결하기위해 컬러정보를 이용하여 교통표지판 영역을 추출하고 추출된 이미지를 인식하는데 다층퍼셉트론 신경망 알고리즘을 적용하여 교통표지판 인식시스템을 제안한다. 제안된 방법은 교통표지판의 컬러를 분석하여 영상에서 교통표지판 영역을 추출한다. 영역을 추출하는 방법은 RGB 컬러 공간으로부터 YUV, YIQ, CMYK 컬러 공간이 가지는 특성을 이용한다. 형태처리는 교통표지판의 기하학적 특성을 이용하여 군집화한다. 교통표지판 인식은 학습이 가능한 다층퍼셉트론의 오류역전파알고리즘을 적용하여 인식한다. 다층퍼셉트론 신경망 알고리즘은 패턴인식 분야에서 우수한 성능이 입증 되었다.

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Study on the Vessel Traffic Safety Assessment for Routeing Measures of Offshore Wind Farm (해상풍력발전단지의 대체통항로 통항안전성 평가에 관한 연구)

  • Yang, Hyoung-Seon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.20 no.2
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    • pp.186-192
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    • 2014
  • In this paper, we analysed vessel traffic volume and patterns of traffic flow for ships using areas where included wind farm site and adjacent waters of Daejeong Offshore Wind Farm, and estimated traffic volume by classified navigational routes according to suggestion of rational routeing measures on the basis of classified patterns after installation of offshore wind facilities. Also, we assessed vessel traffic safety for each designed routeing measures on the basis of estimated traffic volume and proposed requisite countermeasures for the safe navigation of ships. With a result of analysing patterns of traffic flow, the current traffic flow was classified by 8 patterns and the annual traffic volume was predicted to 8,975 ships. On the basis of these, expected the vessel traffic volume according to designed four routeing mesaures after installation of wind farm. As result of assessing vessel traffic safety by using powered-vessel collision model of SSPA on the basis of the estimated traffic volume, the value of collision probability was less than safe criteria $10^{-4}$. Thereby we made sure usability of the designed routeing measures for the safe navigation of ships.

A Estimation Model of The Fuel Consumption Based on The Vehicle Speed Pattern (차량 속도패턴에 따른 연료소모량 관계식 산정)

  • Won, Min-Su;Gang, Gyeong-Pyo;Kim, Jeong-Wan
    • Journal of Korean Society of Transportation
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    • v.29 no.4
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    • pp.65-71
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    • 2011
  • It is practically hard to measure vehicle fuel consumption required to evaluate the energy-related governmental policies and traffic management strategies; the existing methods are too simplified due to the limited field data available. Existing methods are even unable to reflect the amount of fuel consumed when vehicles accelerate and decelerate, and such technical limitations have reduced the quality of the policy evaluation. This study proposes a new fuel consumption model that simultaneously considers the effects of both cruising speed and acceleration/deceleration of vehicles. A new fuel consumption model was developed based on the simulation data generated by AVL Cruise, a vehicle simulation program. The estimated by the proposed model was compared against the one from the existing method. Comparison results showed that the proposed model provided much reliable estimate (fuel consumption) than the other did.

Analysis of Travel Modal Choice and the Temporal Transferability for Workers (취업자의 1일 통행수단선택 분석 및 모형의 시간이전성 검토)

  • 김대웅;배영석;이명미
    • Journal of Korean Society of Transportation
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    • v.17 no.5
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    • pp.19-32
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    • 1999
  • In this study, the trip characteristics of workers in the city are systematically analyzed. The trip behaviors and socioeconomic characteristics of workers are analyzed using Person Trip Survey Data of 1988 and 1992 in Taegu Metropolitan area. With the results of behavioral analyses, the daily travel pattern of workers is shown as one tour contained two trips and it is relatively simple and stable. Also the rate using the same mode in a day is Presented as high ratio. So, it can be explained that the choice of worker\`s first trip is fixed his/her travel mode for his/her daily travel mode. Based on these analyses, the mode choice model for workers is developed by applying the Multi-nominal Logit Model with the choice set of bus, taxi, and car. The explanatory variables of this model include sex, age, auto, travel time, and cost. Empirical tests of the model show encouraging results. After that, the temporal transferability of the model is examined by the Pairwise t-test and five indexes far the model of 1988 and 1992. The results of examination are satisfied with each significance level of the explanatory variables and five indexes. Therefore. it can be concluded that the temporal transferability of this model developed in this study is resonable.

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Estimating the Trip Purposes of Public Transport Passengers Using Smartcard Data (스마트카드 자료를 활용한 대중교통 승객의 통행목적 추정)

  • JEON, In-Woo;LEE, Min-Hyuck;JUN, Chul-Min
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.1
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    • pp.28-38
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    • 2019
  • The smart card data stores the transit usage records of individual passengers. By using this, it is possible to analyze the traffic demand by station and time. However, since the purpose of the trip is not recorded in the smart card data, the demand for each purpose such as commuting, school, and leisure is estimated based on the survey data. Since survey data includes only some samples, it is difficult to predict public transport demand for each purpose close to the complete enumeration survey. In this study, we estimates the purposes of trip for individual passengers using the smart card data corresponding to the complete enumeration survey of public transportation. We estimated trip purposes such as commute, school(university) considering frequency of O-D, duration, and departure time of a passenger. Based on this, the passengers are classified as workers and university students. In order to verify our methodology, we compared the estimation results of our study with the patterns of the survey data.

Fuzzy Control of Elevator Speed Pattern (엘리베이터 속도 패턴의 퍼지 제어)

  • Ahn, Tae-Chon;Kang, Jin-Hyun;Kang, Doo-Young;Yoon, Yang-Woong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.7
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    • pp.857-864
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    • 2004
  • In this paper, a new speed pattern generation method is proposed to offer various speed patterns for the traffic changers, with the comfortable driving and the rapid transportation speed that are two important factors to determine elevator speed pattern. To reduce the speed shift impulse, acceleration and deceleration times are appropriately adjusted to the elevator system when start and stop. In order to improve transportation capability, the jerk is also adjusted to the traffic change. Using fuzzy inference system with 2 input variables and 1 output, the elevator system controls precisely, with the proposed speed pattern.

Multi-Level Models for Activity Participation and Travel Behaviors (다수준 모형을 이용한 활동참여와 통행행태 분석)

  • 최연숙;정진혁;김성호
    • Journal of Korean Society of Transportation
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    • v.20 no.7
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    • pp.79-85
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    • 2002
  • In this paper, multilevel models are adopted to identify interactions among household members in trip making behaviors. The multilevel approach is a proper methodology to handle samples, which are extracted from a hierarchical structure universe. PSTP dataset is used in developing models and understand proportion of variations among individuals and household. The results of this study show that for activity participation and travel behavior household level variance is more than 1/4 of person level variance and therefore not negligible. The results confirm the importance of multilevel model in travel behavior analysis.

Abnormal Behavior Detection and Localization Using Aspect Ratio Based on Mask R-CNN (Mask R-CNN 기반 Aspect Ratio를 활용한 이상행동 검출 및 영역화 방법)

  • Lim, Hyunseok;Hu, Xufeng;Gwak, Jeonghwan
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.01a
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    • pp.99-101
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    • 2022
  • 이상 행동을 탐지하는 딥러닝 기반 검지 시스템은 동영상 기반 데이터로부터 움직임을 보이는 객체를 추적하고 그 객체의 행동을 분석하여 정상적인 행동 범위를 벗어나는 패턴을 보이는 영역을 이상으로 탐지한다. 특히 생성적 적대 신경망(GAN)과 광학 흐름 추정(Optical flow estimation) 기법을 활용하여 움직임에 대한 특징 정보를 추출하고 이를 학습하여 행동 패턴에 대한 모델링을 수행한다. 모델 학습 및 테스트에 활용되는 데이터셋의 해상도가 낮거나 이상 행동을 표현하는 특징 정보가 부족할 경우 최종 모델 성능에 부정적 영향을 미치게 되며, 특히 광학 흐름이 표현하는 이동량 측면에서 차이가 크게 나지 않는 이상 객체의 경우 탐지가 정확하게 이뤄지지 않는다. 본 연구에서는 동영상 프레임에서 나타나는 객체의 평균 종횡비를 구하고 정상적인 비율을 벗어나는 객체에 대해서 이상 행동을 취하는 샘플로 처리하는 후처리단 모듈을 제안하여 최종적인 모델 성능을 향상시키는 방법을 고안한다.

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Development of Web application for railway pattern data approach using Node.js modules (Node.js 모듈을 활용한 철도패턴 데이터 접근을 위한 웹 어플리케이션 개발)

  • HyeonJin Oh;Zhang Yong Heng;Ryumduck Oh
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.119-122
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    • 2023
  • 본 논문에서는 node.js에서 제공하는 oracledb, express, ejs 모듈을 이용해 데이터베이스에 저장되어 있는 철도 패턴 데이터를 라우터를 통해 정해진 경로로 전달하여 ejs 파일로 작성된 페이지에 접근하여 출력하는 웹 애플리케이션을 구현하고자 한다. 웹 애플리케이션의 사용으로 철도 데이터를 필요로 하는 기업이나 사용자가 보다 쉽고 빠르게 데이터를 확인하고, 이를 원하는 방향으로 이용할 수 있다.

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