• 한국도로학회논문집
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• 제17권3호
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• pp.117-124
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• 2015

PURPOSES : The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS : To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS : This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including ${\chi}^2/df$, GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS : Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

• 대한교통학회지
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• 제29권3호
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• pp.73-82
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• 2011

최근 교통상황을 정확하게 관측할 수 있는 교통류 검지에 관한 기술개발과 더불어 개별차량 주행궤적을 이용한 교통안전도 평가기법에 대한 관심이 높아지고 있다. 본 연구에서는 개별차량의 주행궤적을 이용하여 다음시점(t+1) 의 후미추돌 확률을 산출하는 방법론을 제시하였다. 신뢰성 있는 예측 기법인 칼만 필터링(Kalman Filtering)을 이용하여 주행궤적을 예측하고, 예측된 시점에 대한 개별차량의 후미추돌 확률을 산출하였다. 안전도를 평가하는 확률모형을 수립하기 위해서 서해안 고속도로의 동영상 자료로부터 개별차량의 주행궤적을 추출하였다. 추출한 개별차량의 주행궤적 자료를 이항 로지스틱 회귀분석(Binary logistic regression)을 이용하여 차량의 차로변경 결정 확률 모형을 생성하였고, exponential decay function을 이용하여 surrogate safety measure(SSM)의 하나인 time-to-collision(TTC)기반의 추돌확률 모형을 생성하였다. 미시적 교통류 시뮬레이터인 VISSIM에서 추출한 개별차량의 주행궤적 데이터를 이용하여 제안된 방법론을 평가하였다. 본 연구의 결과는 교통류 감시, 제어 및 정보 시스템에 효과적으로 적용될 수 있으며, 나아가 교통사고 예방에 효율적인 대안이 될 수 있을 것으로 판단된다.

• 정보통신설비학회논문지
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• 제8권3호
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• pp.122-131
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• 2009

Ubiquitous-Transportation sensor network is able to realize a vehicle ad-hoc network. Since there are some problems in an existing ITS system, the new technology and traffic information strategies are requirements in this advanced system, u-TSN. The purposes of this paper is to introduce the components on u-TSN system, establish new traffic strategies for this system, and then evaluate these strategies by making a comparative study of ITS and using micro traffic simulator, AIMSUN. The strategy evaluated by AIMSUN is position-based multicast strategy which provides traffic information to vehicles using V2I (vehicle to Infrastructure) communication. This paper focuses on the providing real-time route guidance information when congestion is occurred by the incidents. This study estimates total travel time on each route by API modules. Result from simulation experiments suggests that position-based multicast strategy can achieve more optimal network performance and increased driver satisfaction since the total accumulated travel times of both the major road and the total system on position-based multicast strategy are less than those on VMS.

• 한국자동차공학회논문집
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• 제25권3호
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• pp.317-325
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• 2017

The EDR(Event Data Recorder) is a part of the ACU(Airbag Control Unit) functions mounted on a vehicle. EDR data have pre-crash data and post-crash data. Pre-crash data are recorded within 5 sec from time zero(AE) with 0.5 sec resolution, and reveal vehicle speed, engine rotation speed, throttle opening, brake pedal operation, acceleration pedal position and steering angle, etc. Using this EDR data, the investigation of a traffic accident can become more objective and scientific. Crash tests of three vehicles equipped with EDR function had been performed successfully. Evaluation of EDR data reliability had also been performed using Vbox and PC-Crash's sequence table function. Based on the results, we could confirm EDR data's reliability and availability for Traffic Accident Analysis by the series of this process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.

• 산업공학
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• 제23권4호
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• pp.349-356
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• 2010

The role of Intelligent Transportation System (ITS) is to efficiently manipulate the traffic flow and reduce the cost in logistics by using the state of the art technologies which combine telecommunication, sensor, and control technology. Especially, the hardware part of ITS is rapidly adapting to the up-to-date techniques in GPS and telematics to provide essential raw data to the controllers. However, the software part of ITS needs more sophisticated techniques to take care of vast amount of on-line data to be analyzed by the controller for their decision makings. In this paper, the authors develop a traffic congestion prediction model based on several different parameters from the sensory data captured in the Vehicle Detection System (VDS). This model uses the neural network technology in analyzing the traffic flow and predicting the traffic congestion in the designated area. This model also validates the results by analyzing the errors between actual traffic data and prediction program.

• Wind and Structures
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• 제23권1호
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• pp.19-43
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• 2016

In the present study, a new methodology is presented to study the ride comfort and bridge responses of a long-span bridge-traffic-wind coupled vibration system considering stochastic characteristics of traffic flow and bridge surface progressive deterioration. A three-dimensional vehicle model with 24 degrees-of-freedoms (DOFs) including a three-dimensional non-linear suspension seat model and the longitudinal vibration of the vehicle is firstly presented to study the ride comfort. An improved cellular automaton (CA) model considering the influence of the next-nearest neighbor vehicles and a progressive deterioration model for bridge surface roughness are firstly introduced. Based on the equivalent dynamic vehicle model approach, the bridge-traffic-wind coupled equations are established by combining the equations of motion of both the bridge and vehicles in traffic using the displacement relationship and interaction force relationship at the patch contact. The numerical simulations show that the proposed method can simulate rationally the ride comfort and bridge responses of the bridge-traffic-wind coupled system; and the vertical, lateral, and longitudinal vibrations of the driver seat model can affect significantly the driver's comfort, as expected.

• 한국ITS학회 논문지
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• 제22권1호
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• pp.172-191
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• 2023

본 연구는 국내 자율주행차 시범운행지구 지정 및 운영에 따라 자율주행차 혼재 시 예상되는 교통 변화를 분석하여, 시범운행지구의 자율주행차 혼재 교통운영전략 수립을 목적으로 한다. 시범운행지구가 자율주행차의 안정적 상용화를 위한 테스트 베드로서의 역할을 해내기 위해서는 안전하고 효율적인 교통운영전략 수립이 요구됨에도 현재까지는 자율주행차 혼재에 따른 교통운영전략은 부재하다. 이에 본 연구에서는 자율주행차 혼재 시 자율주행차 시범운행 지구의 교통운영전략을 수립하고자 한다. 자율주행차 도입 단계별 교통운영전략 수립을 위해 자율주행차 혼입률에 따른 교통 효율성 및 안전성 분석을 수행하였으며, 분석 결과를 토대로 자율주행차 혼입률 30%, 70%를 기준으로 도입기, 과도기, 안정기로 구분하였다. 본 연구에서 자율주행차 도입 단계별로 제시한 교통류와 교통안전 관점의 교통운영전략은 다음과 같다. 교통류 운영전략은 자율주행차 도입기에는 기존 도로 인프라 첨단화, 과도기에는 자율주행차 전용차로 및 일반차 마일리지 제도 운영, 안정기에는 자율주행차 전용차로 확대 운영 및 제한속도 완화를 제시하였다. 교통안전 전략은 도입기에는 자율주행차 사고 발생 대응 매뉴얼 및 법 제도 마련, 과도기에는 자율주행차 사고 원인 분석 및 예방정책 시행, 안정기에는 자율주행차 시스템 고도화 및 보안정책 강화를 제시하였다. 본 연구에서 제시한 교통운영전략을 통해 향후 자율주행차 시범운행지구 내 자율주행차 혼재로 인해 예상되는 교통류 및 교통안전 관에서 선제적으로 대응할 수 있을 것으로 기대된다.

• 한국ITS학회 논문지
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• 제19권6호
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• pp.208-221
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• 2020

본 연구는 첨단운전자보조시스템(Advanced Driver Assistance System, ADAS)이 빠르게 보급됨에 따라 표본 프로브 차량에 설치된 ADAS로부터 얻은 개별차량의 궤적 데이터와 전방차량과의 차두거리 데이터를 이용하여 연속류의 교통밀도를 추정 및 분석하는 것을 목적으로 한다. 과거 연속류 교통밀도는 주로 차량검지시스템(Vehicle Detection System, VDS)에서 수집되는 교통량, 속도, 점유율 등의 데이터를 가공하여 추정되거나, CCTV등의 영상정보를 활용하여 직접 차량 대수를 계수하여 추정되었다. 이러한 방식은 교통밀도 추정의 공간적 제약이 있고, 교통 혼잡시 추정의 신뢰도가 낮다는 한계를 보였다. 이에 본 연구에서는 선행연구의 한계를 극복하기 위해 ADAS로부터 수집된 개별차량 궤적 데이터와 차두거리 정보를 활용하여 도로의 공간을 검지하고 일반화된 밀도(Generalized Density)방식을 이용하여 시공간적 교통밀도를 추정한다. 이에 따라 ADAS차량의 표본율에 따른 교통밀도 추정의 정확도를 분석한 결과, 30%의 표본율일 경우 교통밀도 참 값과 약 90% 일치하는 것으로 나타났다. 이를 통해 본 연구는 향후 ADAS 및 자율주행차량이 혼재되는 도로 상황에서 신뢰도 높은 교통밀도 추정을 가능하게 하며 효율적인 교통운영관리에 기여할 수 있을 것으로 판단된다.

• 한국산업융합학회 논문집
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• 제9권4호
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• pp.285-291
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• 2006

A traffic accident is occurred by unbalance of reciprocal action of driver, vehicle and road conditions. To prevent the traffic accident, rapid and perfect road improvement is needed. But most of road improvement plans have insufficient budget. So decision maker has to determine the priority to invest. A model in this study, analyzing the effect of road conditions to the traffic accident, helps to decide the priority in road improvement. This study considered five danger indices ; 1) traffic volume, 2) speed variance, 3) vehicle mixing rate, 4) curved line radius, and 5) difference between design speed and running speed. Danger rate composed by five indices can be a scale of priority of improvement. The model in this study didn't consider all of factors about traffic accident. But this study can propose the methodology for traffic safety policy. For deriving the model, this study used data from highways in Korea and United States. Therefore the model has to apply the highways only.