• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.203-213
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• 2008

U-Turn offers convenience to drivers. U-Turn increases efficiency of traffic flow. But Standard of U-Turn is not clear. It caused many problems of traffic flow and traffic safety. This study estimate length between U-Turn location with front intersection based on stopping sight distance and left-turn vehicle's queue length. Variables are used traffic volume and operation speed. This study Analysis of U-Turn vehicle's behaviors and classification of conflict form by investigation. U-Turn length estimating based on relationship analysis between conflict with U-Turn length. Variables are used lane changing angles and operation speed. This study estimates length between U-Turn location with back intersection based on gap acceptance theory. Variables are used traffic volume, operation speed and lane changing angles. So, U-Turn location and length estimated considering traffic flow and traffic safety.

• Proceedings of the KOR-KST Conference
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• 2003.02a
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• pp.3-18
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• 2003

본 논문은 ATMS와 ATIS에서 요구되는 교통관리 및 정보제공의 효과분석을 위해, 운전자의 주행 및 경로선택 의사결정과 교통제어에 대한 반응등 운전자 행태를 모의실험에 반영함으로써 교통시스템의 실시간 특성을 모사할 수 있는 모형을 구축하고 이를 기반으로 하는 미시적 교통 모의실험기를 개발하는 것을 목적으로 하였다. 본 연구에서는 운전자, 차량, 교통망, 검지 및 신호시스템, 교통정보제공시스템 등을 교통시스템의 주요 구성요소로 설정하였으며 운전자 및 차량특성, 차두시간분포와 차량발생모형, 차량주행모형, 차로변경 및 간격수락모형, 경로선택모형을 주모의실험모형을 구성하는 부모형으로 결정하였다. 따라서 본 논문에서는 각각의 부모형들에 대한 최근의 연구결과들을 검토하고, 현실모사 능력과 함께 다른 부모형들과의 연계, 모의실험기의 구현상에서의 적합성 등을 고려하여 적정모형의 선정 및 수정, 새로운 부모형의 구축을 수행하였다. 구축된 부모형을 통합하여 교통모의실험기를 개발하였으며 구축된 모형의 타당성 및 적용성 검토를 위해 현장자료 및 가상자료를 이용한 검증을 수행하였다. 검증결과 모형의 목적인 교통제어 및 정보제공등의 시스템 대안의 평가에 이용 가능한 것으로 나타났다. 또한 본 논문의 연구결과는 교통제어 및 정보제공전략 대안의 평가뿐만 아니라 차량추종 및 차로변경 등의 미시적 교통모형 연구, 동적기종점 통행량 추정, 동적통행배정의 연구에도 활용할 수 있을 것으로 판단된다. 본 논문의 연구모형은 현단계에서는 현실의 모사 및 분석을 위한 도구보다는 새로운 대안들간의 비교평가를 위한 도구로 활용할 수 있을 것으로 판단된다. 이에 따라 현실모사의 정확도를 확보하기 위한 검증 및 개선이 필요할 것이며, 각 부모형들에 대한 계속적인 연구와 새롭게 발표되는 연구결과를 수용한 지속적인 개발이 필요할 것이다.유기적인 연계에 있음을 밝히고 있다. 건설을 위한 정책적 시사점과 동북아 연구개발정보 Portal 및 APEC APGrid 연구망 등의 구체적인 정보인프라 구축방안을 도출하였다.술 주기를 도출하고, 산업 내 평균 권리 청구 항목 수를 이용하여 각 산업의 기술 범위를 비교하였다. 각각의 동적 분석을 통해 시간에 따른 변화 양상이 관찰하였고, ANOVA 분석을 이용하여 통계적 유의성을 검증하였다. 본 연구는 현재의 기술 패러다임 내에서 Pavitt이 제시한 산업 분류의 근거를 보충 설명하였고 특허 정보를 이용하여 기술혁신의 산업별 유형에 대한 폭넓은 분석방법을 제시하였다.별 시간대별 효과분석을 통하여 정책의 시행여부가 결정되어야 할 것이다. 한편, 화물전용차선의 설치로 인한 물류비용의 절감을 보다 효과적으로 달성하기 위해서는 종합류류 전산망의 시급한 구축과 함께 화물차의 적재율을 높이고 공차율을 낮출 수 있는 운송체계의 수립이 필요한 것으로 판단된다. 그라나 이러한 화물전용차선의 효과는 단기적인 치유책일 수밖에 없기 때문에 물류유통 시설의 확충을 위한 사회간접자본의 구축을 서둘러 시행하여야 할 것이다.으로 처리한 Machine oil, Phenthoate EC 및 Trichlorfon WP는 비교적 약효가 낮았다.>$^{\circ}$E/$\leq$30$^{\circ}$NW 단열군이 연구지역 내에서 지하수 유동성이 가장 높은 단열군으로 추정된다. 이러한 사실은 3개 시추공을 대상으로 실시한 시추공 내 물리검층과 정압주입시험에서도 확인된다.. It was resulted from increase of weight of single cocoon. "Manta"2.5ppm produced 22.2kg of cocoon. It is equal to 9%

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.66-83
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• 2021

Vehicles experience changes in driving behavior due to the various facilities on the freeway. These sections may cause repetitive traffic congestion when the traffic volume increases, so safety issues may be raised. Therefore, the purpose of this study is to perform microscopic traffic analysis on these sections using drone images and to identify the causes of traffic problems. In the case of drone image, since trajectory data of individual vehicles can be obtained, empirical analysis of driving behavior is possible. The analysis section of this study was selected as the weaving section of Pangyo IC and the sag section of Seohae Bridge. First, the trajectory data was extracted through the drone image. And the microscopic traffic analysis performed on the speed, density, acceleration, and lane change through cell-unit analysis using Generalized definition method. This analysis results can be used as a basic study to identify the cause of the problem section in the freeway. Through this, we aim to improve the efficiency and convenience of traffic analysis.

• Spatial Information Research
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• v.23 no.4
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• pp.79-89
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• 2015

This study aims to design and implement a traffic model that can simulate the traffic behavior on the microscopic level by using the GIS. In the design of the model, the vehicle in the simulation environment recognizes the GIS road centerline data as road network data reflecting number of lanes, speed limit and so on. In addition, the behavior model was designed by dividing functions into the environmental perception model, time headway distribution model, car following model, and lane changing model. The implemented model was applied to Jahamun-road of Jongno-gu district to verify the accuracy of the model. As a result, the simulation results on the Jahamun-road had no great error compared with the actual observation data. In the aspect of usability of model, it is judged that this model will be able to effectively contribute to analysis of amount of carbon emission by traffic, evaluation of traffic flow, plans for location of urban infrastructure and so on.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.42-60
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• 2024

This study analyzed the characteristics of mixed traffic flows with autonomous vehicles on highway weaving sections and assessed the safety of vehicle-following pairs based on surrogate safety indicators. The intelligent driver model (IDM) was utilized to emulate the driving behavior of autonomous vehicles, and the weaving sections were divided into lengths of 300 and 600 meters for analysis within a micro-traffic simulation (VISSIM). Although significant differences were found in the average speed, density, and headway between the two sections through t-test results, no significant differences were observed when comparing the number of conflicts per indicator and the vehicle-following pair. Four safety indicators were selected for the mixed traffic evaluation based on their ability to represent risk levels similar to those perceived by drivers. The safety analysis, based on the selected four indicators, determined that autonomous vehicles following other autonomous vehicles were the safest pairing. Future research should focus on integrating these indicators into a single comprehensive index for analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.132-145
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• 2022

This study was based on the black box images of traffic accidents on highways, cluster analysis and prediction model comparisons were carried out. As analysis data, vehicle driving behavior and road surface conditions that can grasp road and traffic conditions just before the accident were used as explanatory variables. Considering that traffic accident data is affected by many factors, cluster analysis reflecting data heterogeneity is used. Each cluster classified by cluster analysis was divided based on the ratio of the severity level of the accident, and then an accident prediction evaluation was performed. As a result of applying the Logit model, the accident prediction model showed excellent predictive ability when classifying groups by cluster analysis and predicting them rather than analyzing the entire data. It is judged that it is more effective to predict accidents by reflecting the characteristics of accidents by group and the severity of accidents. In addition, it was found that a collision accident during stopping such as a secondary accident and a side collision accident during lane change act as important driving behavior variables.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.97-114
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• 2022

Unlike ground roads, the on-ramp merging section of underground roads cannot be seen by drivers of main road due to tunnels. In this study, a driving simulator was used for analysis, and virtual driving experiments were carried out to assess the driver's visibility for different design factors. The driver's driving behavior was analyzed by setting scenarios considering the length of chevron markings and the approach speed from the main road. The results of the analysis were used to determine the design factors for ensuring visibility when constructing the virtual driving environment for each scenario. These factors, including speed, lane change points, and driver's gaze ratios, were reviewed for significance using a statistical approach. As a result, in scenarios with a higher approach speed from the main road, it was discovered that there was a difference in driver's behavior between specific scenarios depending on the length of the section with chevron markings. Based on these findings, this study suggests implications and feasible solutions to improve driver safety on the on-ramp merging section of underground roads.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.545-556
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• 2017

Various assessment indexes have been developed and utilized to evaluate the driver workload. However, existing workload assessment indexes do not fully reflect driving habits and driving patterns of individual drivers. In addition, there exists significant differences in the amount of workload experienced by a driver and the ability to overcome the driver's workload. To overcome these limitations associated with existing indexes, this study has developed a novel workload assessment index to reflect an individual driver's driving pattern. An average of the absolute values of the steering velocity for each driver are set as a threshold value in order to reflect the driving patterns of individual drivers. Further, the sum of the areas of the steering velocities exceeding the threshold value, which is defined as erratic steering area (ESA) in this study, was quantified. The developed ESA index is applied in evaluating the driver workload of manually driven vehicles in automated vehicle platooning environments. Driving simulation experiments are conducted to collect drivers' responsive behavior data which are used for exploring the relationship between the NASA-TLX score and the ESA by the correlation analysis. As a result, ESA is found to have the greatest correlation with the NASA-TLX score among the various driver workload evaluation indexes in the lane change scenario, confirming the usefulness of ESA.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.121-138
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• 2011

More affordable and available cutting-edge technologies (e.g., wireless vehicle communication) are regarded as a possible alternative to the fixed infrastructure-based traffic information system requiring the expensive infrastructure investments and mostly implemented in the uninterrupted freeway network with limited spatial system expansion. This paper develops an advanced decentralized traveler information System (ATIS) using vehicle-to-vehicle (V2V) communication system whose performance (drivers' travel time savings) are enhanced by three complementary functions (autonomous automatic incident detection algorithm, reliable sample size function, and driver behavior model) and evaluates it in the typical $6{\times}6$ urban grid network with non-recurrent traffic state (traffic incident) with the varying key parameters (traffic flow, communication radio range, and penetration ratio), employing the off-the-shelf microscopic simulation model (VISSIM) under the ideal vehicle communication environment. Simulation outputs indicate that as the three key parameters are increased more participating vehicles are involved for traffic data propagation in the less communication groups at the faster data dissemination speed. Also, participating vehicles saved their travel time by dynamically updating the up-to-date traffic states and searching for the new route. Focusing on the travel time difference of (instant) re-routing vehicles, lower traffic flow cases saved more time than higher traffic flow ones. This is because a relatively small number of vehicles in 300vph case re-route during the most system-efficient time period (the early time of the traffic incident) but more vehicles in 514vph case re-route during less system-efficient time period, even after the incident is resolved. Also, normally re-routings on the network-entering links saved more travel time than any other places inside the network except the case where the direct effect of traffic incident triggers vehicle re-routings during the effective incident time period and the location and direction of the incident link determines the spatial distribution of re-routing vehicles.