• Title/Summary/Keyword: Traffic estimation

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Analysis of Spatial Trip Regularity using Trajectory Data in Urban Areas (도시부 경로자료를 이용한 통행의 공간적 규칙성 분석)

  • Lee, Su jin;Jang, Ki tae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.6
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    • pp.96-110
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    • 2018
  • As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

A Study on Estimation of Road and Transportation Facility Improvement Direction Using Random Forest (랜덤 포레스트를 활용한 도로 및 교통시설 개선방향 추정 연구)

  • Hwang, Jae-seong;Kim, Do-kyeong;Kim, Nam-sun;Lee, Choul-ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.37-46
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    • 2021
  • Government agencies, such as police and local governments, strive to prevent traffic hazards and create a comfortable road environment by pormoting transportation and road facilities. To this end, roads and transportation facilities are enhanced and adjusted, and improvement projects in areas with frequent traffic accidents are carried out. Usually, improvement projects in areas with frequent traffic accidents vary by projects and region. Moreover, these projects are carried out under the supervision of a person in charge and related parties. Hence, civil complaints and subjectivity are reflected in deriving priorities for the improvement projects, limiting the efficiency of the project. To this end, a study was conducted to estimate the direction of improvement of the project target site. This study comprehensively considered road, traffic, and accident conditions of representative projects with high effectiveness in handling traffic accidents. The results of the study state that the accuracy of estimating the improvement project was around 88%. In addition, the study found that there was a strong relationship between traffic volume, accident rate, and accident severity in estimating the improvement direction.

Development of Travel Time Estimation Algorithm for National Highway by using Self-Organizing Neural Networks (자기조직형 신경망 이론을 이용한 국도 통행시간 추정 알고리즘)

  • Do, Myungsik;Bae, Hyunesook
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.3D
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    • pp.307-315
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    • 2008
  • The aim of this study is to develop travel time estimation model by using Self-Organized Neural network(in brief, SON) algorithm. Travel time data based on vehicles equipped with GPS and number-plate matching collected from National road number 3 (between Jangji-IC and Gonjiam-IC), which is pilot section of National Highway Traffic Management System were employed. We found that the accuracies of travel time are related to location of detector, the length of road section and land-use properties. In this paper, we try to develop travel time estimation using SON to remedy defects of existing neural network method, which could not additional learning and efficient structure modification. Furthermore, we knew that the estimation accuracy of travel time is superior to optimum located detectors than based on existing located detectors. We can expect the results of this study will make use of location allocation of detectors in highway.

Estimation of Mean Life and Reliability of Highway Pavement Based on Reliability Theory (신뢰성 개념을 이용한 포장의 평균수명 및 신뢰도 예측)

  • Do, Myung-Sik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.5D
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    • pp.497-504
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    • 2010
  • In this paper, the author presents a reliability estimation technique to analyze the effects of traffic loads on pavement mean life based on the national highway database of Suwon and Uijeongbu region from 1999 to 2008. The estimation of the mean life, its standard deviation and reliability for pavement sections are calculated by using an appropriate distribution, Lognormal distribution, based on reliability theory. Furthermore, the probability paper method and Maximum likelihood estimation are both used to estimate parameters. The author found that mean life of newly constructed sections and over-layed sections is about 6.5 to 7.9 years and 7.3 to 9.1 years, respectively. The author also ascertained that the results of cumulative failure probability for pavement life between the proposed methods and observed data are similar. Such an assessment methodology and measures based on reliability theory can provide useful information for maintenance plans in pavement management systems as long as additional life data on pavement sections are accumulated.

Estimation of AADT Using Multiple Linear Regression in Isolated Area (다중선형 회귀분석을 이용한 고립지역에서의 AADT 추정방안 연구)

  • Kim, Tae-woon;Oh, Ju-sam
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.35 no.4
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    • pp.887-896
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    • 2015
  • This study estimates future AADT using historical AADT and socio-economic factors in isolated area. Multiple linear regression method by socio-economic factors are lower MAPE and higher R-square than using historical AADT. Analysis of socio-economic factors influence AADT in isolated typical areas, varied socio-economic factors influence on AADT. In isolated coastal areas, oil price influence on AADT. AADT forecasting model in isolated area is excellent when analysising $R^2$ and MAPE. It is assume that estimation of AADT in isolated area using multiple linear regression is accurate because of a little passed traffic volume and traffic volume fluctuation.

A Study on the Estimation Method of Operational Delay Cost in Bus Accidents using Transportation Card Data (교통카드자료를 이용한 버스 사고 시 운행지연비용 산정 방법론에 관한 연구)

  • Seo, Ji-Hyeon;Lee, Sang-Soo;Nam, Doohee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.5
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    • pp.29-38
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    • 2018
  • This study aims to propose a method for the estimation of operational delay cost using transportation card data in bus accidents. Average operational delay time from bus accidents was surveyed among 12 bus companies through an interview method. Then, the operational delay cost was estimated using actual traffic accident data and transportation card data. Results showed that average loss time per bus accident was found to be 45 minutes. In addition, total occupancy of 659 was estimated for the accidents investigated using transportation card data, resulting a total loss time of 494.25 hours. An estimated operational delay cost was 186.9 thousand won per accident, which was 6.37% of social agency cost. The magnitude of this number implied that operational delay cost may have a significant impact on traffic accident cost if included.

Development of Regression Model to evaluate the indirect costs of Life-Cycle Costs (생애주기비용의 간접비용 산출을 위한 Regression Model의 개발)

  • 조효남;이종순;김충완;박경훈
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.10a
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    • pp.150-156
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    • 2004
  • Though the concept of Life-Cycle Cost (LCC) itself is not new, its effectiveness for planning, design, rehabilitation and maintenance/management of civil infrastructures is becoming increasingly recognized. For the decision problems as in the case of the LCC of plant facilities, equipments, bridge decks, pavements, etc., the Life-Cycle Cost Analysis (LCCA) is relatively simple, and thus its practical implementation is rather straightforward. However, when it comes to major infrastructures such as bridge, tunnels, underground facilities, etc., the LCCA problem becomes extremely complex because lack of cost data associated with various direct and indirect losses, and the absence of uncertainty data available for the assessment as well. As a result, the LCC studies have been largely limited only to those relatively simple LCCA problems of planning or conceptual design for making decisions. Accordingly, in the recent years, the researchers have pursued extensive studies on the LCC effectiveness mostly related to LCC models and frameworks for civil infrastructures. Moreover, recently the demand on the practical application of LCC effective decisions in design and maintenance is rapidly growing unprecedently in civil engineering practice. Indirction cost is very important on LCC formulation. But that is very difficult and complicate the estimation every LCC. The objective of this paper is to suggest efficient regression model for the estimation of indirect cost approach to the practical application of LCC for the design and rehabilitation of civil. infrastructures considering traffic, traffic network, detour condition, and workzone condition. In this paper, it performed the sensitivity analysis and correlation analysis of parameter for development of regression model of inflection cost.

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Speed Estimation by Applying Volume Weighted Average Methods in COSMOS (교통량 가중평균 방법을 적용한 COSMOS 속도 추정)

  • Lee Sang-soo;Lee Seung-hwan;Oh Young-Tae;Song Sung-ju
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.2 no.1 s.2
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    • pp.63-73
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    • 2003
  • COSMOS(Cycle, Offset, Split Model for Seoul), a real-time traffic adaptive signal system. estimates queue lengths on each approach on the basis of arithmetic average spot speeds calculated on loop detectors installed at each of two adjacent lanes. In this paper, A new method, a traffic volume-weighted average method, was studied and compared with the existing arithmetic average method. It was found that the relationship between the ratio of volumes of two lanes and the difference of average speed of each lane has a linear form. With field data, The two methods were applied and the proposed method shows more stable and reasonable queue estimation results.

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Statistical analysis and probabilistic modeling of WIM monitoring data of an instrumented arch bridge

  • Ye, X.W.;Su, Y.H.;Xi, P.S.;Chen, B.;Han, J.P.
    • Smart Structures and Systems
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    • v.17 no.6
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    • pp.1087-1105
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    • 2016
  • Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

On an Algorithm for the Assessment of Collision Risk among Multiple Ships based on AIS (AIS 기반 다중선박 충돌 위험도 추정 알고리즘에 관한 연구)

  • Son, Nam-Sun;Oh, Jae-Yong;Kim, Sun-Young
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2009.10a
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    • pp.62-63
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    • 2009
  • A monitoring system of collision risk among multiple ships is newly-designed in order to reduce human error and make vessel traffic control more effective. By using AIS data as ships' navigational information, an estimation algorithm of collision risk among multiple ships is newly-designed. To consider ships' course of now and future, collision risks of multiple ships can be calculated by using fuzzy algorithm. To test the performance of new algorithm, replay simulations are carried out on actual AIS data collected from VTS center of Ulsan harbor in Korea. The AIS data include 25 ships' information for two hours. In this paper, the features of newly-designed estimation algorithm of collision risk and the results of replay simulation are discussed.

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