• Title/Summary/Keyword: estimation data traffic

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A Study on Estimate to Link Travel Time Using Traveling Data of Bus Information System (버스정보시스템(BIS) 운행자료를 이용한 링크통행시간 추정)

  • Lee, Young Woo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3D
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    • pp.241-246
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    • 2010
  • This study is to estimate the link travel time of road networks in urban areas utilizing traffic information which is collected throughout the operation of Bus Information System (BIS). BIS, which applies the hightech information technology to an existing bus system, has been developing and operating in many bodies including the local self-government entities. However, a study to consider the technology trend is relatively rare. Even though some useful traffic informations have been collected throughout the operation of an existing BIS, which set limits to the development of a future service of integrated analysis. Accordingly, in this study, a fundamental research is performed for traffic controls in urban areas and providing a traffic information for driver throughout the estimation of link travel time of road networks. The study is proceeded throughout the data collected from the operation of BIS (Bus Information System). The result showed that the patterns of going through traffic were divided up to 2 in the bus travel time in BIS then estimate two link travel time.

Development and Validation of an Improved 5-DOF Aircraft Dynamic Model for Air Traffic Control Simulation (항공교통관제 시뮬레이션을 위한 개선된 5 자유도 항공기 운동 모델 개발 및 검증방안 연구)

  • Kang, Jisoo;Oh, Hyeju;Choi, Keeyoung;Lee, Hak-Tae
    • Journal of Advanced Navigation Technology
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    • v.20 no.5
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    • pp.387-393
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    • 2016
  • To perform realistic air traffic control (ATC) simulation in various air traffic situations, an aircraft dynamic model that is accurate and efficient is required. In this research, an improved five degree of freedom (5-DOF) dynamic model with feedback control and guidance law is developed, which utilizes selected performance data and operational specifications from the base of aircraft data (BADA) and estimations using aircraft design techniques to improve the simulation fidelity. In addition, takeoff weight is estimated based on the aircraft type and flight plan to improve simulation accuracy. The dynamic model is validated by comparing the simulation results with recorded flight trajectories. An ATC simulation system using this 5-DOF model can be used for various ATC related research.

Statistical models from weigh-in-motion data

  • Chan, Tommy H.T.;Miao, T.J.;Ashebo, Demeke B.
    • Structural Engineering and Mechanics
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    • v.20 no.1
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    • pp.85-110
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    • 2005
  • This paper aims at formulating various statistical models for the study of a ten year Weigh-in-Motion (WIM) data collected from various WIM stations in Hong Kong. In order to study the bridge live load model it is important to determine the mathematical distributions of different load affecting parameters such as gross vehicle weights, axle weights, axle spacings, average daily number of trucks etc. Each of the above parameters is analyzed by various stochastic processes in order to obtain the mathematical distributions and the Maximum Likelihood Estimation (MLE) method is adopted to calculate the statistical parameters, expected values and standard deviations from the given samples of data. The Kolmogorov-Smirnov (K-S) method of approach is used to check the suitability of the statistical model selected for the particular parameter and the Monte Carlo method is used to simulate the distributions of maximum value stochastic processes of a series of given stochastic processes. Using the statistical analysis approach the maximum value of gross vehicle weight and axle weight in bridge design life has been determined and the distribution functions of these parameters are obtained under both free-flowing traffic and dense traffic status. The maximum value of bending moments and shears for wide range of simple spans are obtained by extrapolation. It has been observed that the obtained maximum values of the gross vehicle weight and axle weight from this study are very close to their legal limitations of Hong Kong which are 42 tonnes for gross weight and 10 tonnes for axle weight.

Laser Scanner based Static Obstacle Detection Algorithm for Vehicle Localization on Lane Lost Section (차선 유실구간 측위를 위한 레이저 스캐너 기반 고정 장애물 탐지 알고리즘 개발)

  • Seo, Hotae;Park, Sungyoul;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.9 no.3
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    • pp.24-30
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    • 2017
  • This paper presents the development of laser scanner based static obstacle detection algorithm for vehicle localization on lane lost section. On urban autonomous driving, vehicle localization is based on lane information, GPS and digital map is required to ensure. However, in actual urban roads, the lane data may not come in due to traffic jams, intersections, weather conditions, faint lanes and so on. For lane lost section, lane based localization is limited or impossible. The proposed algorithm is designed to determine the lane existence by using reliability of front vision data and can be utilized on lane lost section. For the localization, the laser scanner is used to distinguish the static object through estimation and fusion process based on the speed information on radar data. Then, the laser scanner data are clustered to determine if the object is a static obstacle such as a fence, pole, curb and traffic light. The road boundary is extracted and localization is performed to determine the location of the ego vehicle by comparing with digital map by detection algorithm. It is shown that the localization using the proposed algorithm can contribute effectively to safe autonomous driving.

Design Hourly Factor Estimation with Vehicle Detection System (차량검지기자료를 이용한 고속도로 설계시간계수 산정 연구)

  • Baek, Seung-Geol;Kim, Beom-Jin;Lee, Jeong-Hui;Son, Yeong-Tae
    • Journal of Korean Society of Transportation
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    • v.25 no.6
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    • pp.79-88
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    • 2007
  • Design Hourly Volume (DHV) is the hourly volume used for designing a section of road. DHV is also used to estimate the expected number of vehicles to pass or traverse the relevant section of road in a future target year. The Design Hour Factor (DHF) is defined as the ratio of DHV to Average Annual Daily Traffic (AADT). In addition to high precision of predicted traffic volume, in order to design a roadway to be the proper scale, applying appropriate DHFs considering traffic flow characteristics and type of area which surrounds the relevant roadway is important. This study categorizes sections of expressway (Suh Hae An Expressway) according to their area type and estimates DHFs utilizing traffic data obtained from a vehicle detection system (VDS). This study shows that DHFs calculated using VDS data are different from those using traffic data acquired from a coverage survey. While AADTs from both data show similar values, peak hour volumes from both data show significant differences especially for recreational areas. DHFs from the coverage survey are quite different from the values provided by the Korean design guide or previous research results and DHFs for urban areas are higher than recreational areas. However, DHFs from VDS shows similar values to previous research results. The result of this study suggests that using VDS for estimating DHFs is more reliable than using a coverage survey.

Railway Noise Exposure-response Model based on Predicted Noise Level and Survey Results (예측소음도와 설문결과를 이용한 철도소음 노출-반응 모델)

  • Son, Jin-Hee;Lee, Kun;Chang, Seo-Il
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.21 no.5
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    • pp.400-407
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    • 2011
  • The suggested method of previous Son's study dichotomized subjective response data to modeling noise exposure-response. The method used maximum liklihood estimation instead of least square estimation and the noise exposure-response curve of the study was logistic regression analysis result. The method was originated to modeling community response rate such as %HA or %A. It can be useful when the subjective response was investigated based on predicted noise level. It is difficult to measure the single source emitting noise such as railway because various traffic noise sources combined in our life. The suggested method was adopted to model in this study and railway noise-exposure response curves were modeled because the noise level of this area was predicted data. The data of this study was used by previous Ko's paper but he dealt the area as combined noise area and divided the data by dominant noise source. But this study used all data of this area because the annoyance response to railway noise was higher than other noise according to the result of correlation analysis. The trend of the %HA and %A prediction model to train noise of this study is almost same as the model based on measured noise of previous Lim's study although the investigated areas and methods were different.

Development of Traffic Accident Prediction Models Considering Variations of the Future Volume in Urban Areas (신설 도시부 도로의 장래 교통량 변화를 반영한 교통사고 예측모형 개발)

  • Lee, Soo-Beom;Hong, Da-Hee
    • Journal of Korean Society of Transportation
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    • v.23 no.3 s.81
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    • pp.125-136
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    • 2005
  • The current traffic accident reduction procedure in economic feasibility study does not consider the characteristics of road and V/C ratio. For solving this problem, this paper suggests methods to be able to evaluate safety of each road in construction and improvement through developing accident Prediction model in reflecting V/C ratio Per road types and traffic characters. In this paper as primary process, model is made by tke object of urban roads. Most of all, factor effecting on accident relying on road types is selected. At this point, selecting criteria chooses data obtained from road planning procedure, traffic volume, existence or non-existence of median barrier, and the number of crossing point, of connecting road. and of traffic signals. As a result of analyzing between each factor and accident. all appear to have relatives at a significant level of statistics. In this research, models are classified as 4-categorized classes according to roads and V/C ratio and each of models draws accident predicting model through Poisson regression along with verifying real situation data. The results of verifying models come out relatively satisfactory estimation against real traffic data. In this paper, traffic accident prediction is possible caused by road's physical characters by developing accident predicting model per road types resulted in V/C ratio and this result is inferred to be used on predicting accident cost when road construction and improvement are performed. Because data using this paper are limited in only province of Jeollabuk-Do, this paper has a limitation of revealing standards of all regions (nation).

The Estimation of the Future Container Ship Traffic for Three Major Ports in Korea (국내 3대 주요 컨테이너항만의 장래 컨테이너선박 교통량 추정)

  • Kim, Jung-Hoon
    • Journal of Navigation and Port Research
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    • v.31 no.5 s.121
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    • pp.353-359
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    • 2007
  • Effective plan and operation managements can be established in advance if the traffic volume of container ship will be forecasted in the trend for container port's cargo volume to increase. At the viewpoint for marine traffic the number of incoming and outgoing container ship can be presumed in the long run and organised rational plan to deal the demand of marine traffic on the basis. Therefore, the paper estimated the future traffic volume of incoming and outgoing container ship for Busan, Gwangyang, and Incheon port on a forecasting data basis of container volume suggested in the national ports base plan. The trends of volume per ship on container were estimated with ARIMA models and seasonal index was computed. Thus the traffic volume of container ship in the future was estimated computing with volume per ship in 2011,2015, and 2020 respectively.

Improvement of Multivariable, Nonlinear, and Overdispersion Modeling with Deep Learning: A Case Study on Prediction of Vehicle Fuel Consumption Rate (딥러닝을 이용한 다변량, 비선형, 과분산 모델링의 개선: 자동차 연료소모량 예측)

  • HAN, Daeseok;YOO, Inkyoon;LEE, Suhyung
    • International Journal of Highway Engineering
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    • v.19 no.4
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    • pp.1-7
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    • 2017
  • PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

A Study on Improving Reliability of Benefit Estimation Based on User Equilibrium Traffic Assignment Results (이용자 균형 통행배정 결과를 이용한 편익추정의 안정성 제고방안 연구)

  • Kim, Jae-Yeong;Son, Ui-Yeong
    • Journal of Korean Society of Transportation
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    • v.25 no.6
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    • pp.19-31
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    • 2007
  • When estimating the benefits from an investment project in the transportation sector, errors caused by many factors may exist. This study focuses on user equilibrium traffic assignment methods and stopping criteria. According to previous studies, when using a user equilibrium assignment model, the benefits of travel time savings can be effected by the relative gap value. As the stopping criteria decreases, the time needed for traffic assignment increases, so that lowering the criteria cannot be the best solution. Therefore, an effort is necessary to reduce this change rate and thus improve reliability. This paper considers three methods: reducing the links subject to benefit calculation, extracting sub-area O/D tables and networks, and applying the mean value of successive traffic assignment results. The results of the analysis show that the method using the mean value of five results is more proper than the other methods. Using the sub-area analysis method, if the study area is small the benefits of a project might be over- or under-estimated. This paper used a nationwide O/D table and network at peak time as a case study. The resulting patterns can differ according to basic data to be used in analysis. So further analysis using the data from metropolitan areas are needed.