• Title/Summary/Keyword: Road traffic accidents

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Detection of Visual Attended Regions in Road Images for Assisting Safety Driving (안전 운전 지원을 위한 도로 영상에서 시각 주의 영역 검출)

  • Kim, Jong-Bae
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.1
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    • pp.94-102
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    • 2012
  • Recently entered into an aging socity as the number of elderly drivers is increasing. Traffic accidents of elderly drivers are caused by driver inattentions such as poor vehicle control due to aging, visual information retrieval problems caused by presbyopia, and objects identifying problems caused by low contrast sensitivity. In this paper, detection method of ROIs on the road is proposed. The proposed method creates the saliency map to detect the candidate ROIs from the input image. And, the input image is segmented to obtain the ROIs boundary. Finally, selective visual attention regions are detected according to the presence or absence of a segmented region with saliency pixels. Experimental results from a variety of outdoor environmental conditions, the proposed method presented a fast object detection and a high detection rate.

Analysis of Deep Learning Model for the Development of an Optimized Vehicle Occupancy Detection System (최적화된 차량 탑승인원 감지시스템 개발을 위한 딥러닝 모델 분석)

  • Lee, JiWon;Lee, DongJin;Jang, SungJin;Choi, DongGyu;Jang, JongWook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.1
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    • pp.146-151
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    • 2021
  • Currently, the demand for vehicles from one family is increasing in many countries at home and abroad, reducing the number of people on the vehicle and increasing the number of vehicles on the road. The multi-passenger lane system, which is available to solve the problem of traffic congestion, is being implemented. The system allows police to monitor fast-moving vehicles with their own eyes to crack down on illegal vehicles, which is less accurate and accompanied by the risk of accidents. To address these problems, applying deep learning object recognition techniques using images from road sites will solve the aforementioned problems. Therefore, in this paper, we compare and analyze the performance of existing deep learning models, select a deep learning model that can identify real-time vehicle occupants through video, and propose a vehicle occupancy detection algorithm that complements the object-ident model's problems.

Analysis of the Cause of Defects in Asphalt Pavement Using Steel Slag as Auxiliary Base Material (보조기층재로 제강슬래그가 사용된 아스팔트 포장면 불량 원인 분석)

  • Jang, Jeong-Wook
    • The Journal of the Korea Contents Association
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    • v.22 no.10
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    • pp.546-553
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    • 2022
  • This research has focused on identifying a significant cause of the pavement cracks and irregularities of roads in Changwon city which have been constructed using steel slag, an auxiliary-based material. It is important to note that the cracks and irregularities yield logistics inconvenience, the risk of traffic accidents, and increased road maintenance costs. X-ray diffraction analysis tests have been conducted in this study on the sample collected by pavement cutting and excavating the three target roads. It is well known that the primary cause of the expansion of steelmaking slag is the hydration reaction between CaO and MaO. While the reaction of CaO is completed within a few months, that of MgO is pretty slow depending on the firing temperature. The test results reveal that the MgO content of the testing samples is approximately 47% of the total average, and that of CaO is around 14% of the total average. Hence, these results make it possible to be understood that the expansion induced by the slow hydration reaction of MgO results in road uplift in the long term, resulting in the cracks and irregularities of roads.

Development of Measure of Effectiveness (MOE) and Algorithm for Hazard Level at Curve Sections (곡선부 위험도 판정척도 및 알고리즘 개발)

  • Ha, Tae-Jun;Jeong, Jun-Hwa;Lee, Jeong-Hwan;Lee, Suk-Ki
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5D
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    • pp.627-638
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    • 2008
  • At present, there is a no rational MOE for evaluating hazard level at curve sections. Therefore, this study focus on developing the MOE and algorithm for hazard level at curve sections. The scopes of this study limited to rural two-way roads. Actual data used is accident, geometric features, safety facilities of the selected sites at curve sections. In order to develop MOE for hazard level at curve sections, accident contributing factors were classified by road geometry, visual guidance facility, speed and driver factor. A relationship between the four factors mentioned and accidents was conducted. And, the MOE for hazard level at curve sections was derived from the previous relationship analysis, and the algorithm for hazard level was developed. Finally, worksheets were suggested based on the MOE and algorithm for road designers. These developed MOE and algorithm can be used to reduce serious accident contributing factors when designing roads and also, these will be used to determine an order of priority when reconstructing roads.

Accident Reduction Effects by year After Installation of Red Light Cameras (무인신호위반단속장비 설치 후의 연도별 사고감소 효과)

  • Kim, Tae-Young;Park, Byung-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.9 no.2
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    • pp.23-32
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    • 2010
  • Because ROTA(road traffic authority) analyzes the effects of accident reduction based on the data of 1-year after installation of RLC(red light camera), study of accident reduction effects over year after the installation of RLC is very short. This study deals with the traffic accident reduction during 3 years after the installation of RLC. The objective is to analyze the effects of accident reduction by year using EB method. In pursuing the above, the study uses the 951 accident data occurred at the 20 intersections which RLC are installed. The main results analyzed are as follows. First, the safety performance function (SPF) has been developed by the Poisson regression models which are statistically significant. Second, the results of an Empirical Bayes(EB) analyses showed that the accidents were reduced by the range from 2.73 to 38.75% after 1 year, from 6.85 to 47.36% after 2 year, and from 6.04 to 39.31% after 3 year from the installation of RLC.

Analysis of Dilemma Zone Safety Considering Signal Location (신호기 위치에 따른 딜레마존 안전율 분석)

  • Ryu, Chang-Nam;Kim, Won-Chul;Jang, Tae-Youn;Lim, Sam-Jin
    • Journal of Korean Society of Transportation
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    • v.26 no.1
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    • pp.7-14
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    • 2008
  • One of purposes of installing signals at intersections is to protect traffic conflicts and accidents from occurring by means of arranging the right-of-way of travel more clearly. On the other hand, the installation of signals, and especially their location, can also have negative effects on safety. Therefore, the location of signals is of great importance. To secure a high safety level for urban signalized intersection, efforts are required to introduce a comprehensive recommendation or guideline for safety aspects of signal installation that takes local conditions into account. In this context, this reports on a study that analyzed the influence of signal location on the behavior of drivers who approach a signalized intersection in urban area. As a result, the study found out that the traffic signal location strongly affects the braking point of the Dilemma Zone(DZ), and the braking point of the DZ based on driving speed. Also, in terms of design layout, it has been illustrated that there is a close relation between signal location and road safety, especially DZ safety. Finally, this paper proposes a practical recommendation for signal installation related to how to locate the signal in practice for the sake of securing the safety level of signalized intersection.

Construction of Multimedia Information System to Guide Urban Information - at the city of Chin-ju - (도시정보안내를 위한 멀티미디어 정보시스템구축 - 진주시를 중심으로 -)

  • 유환희;조해용;김성우
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.15 no.1
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    • pp.63-73
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    • 1997
  • The objective for the plan of informatization which the government earring out is the modernization of the in-formation service system to be diverse and speedy. With the increase in variety and volume of the available in-formation at the city now, it has become necessary to develop more efficient system of offering the various displays by using computer graphics and multimedia functions as well as storing and managing the information. The multimedia urban information system, which we developed, was designed to furnish various informations of the city to the citizens more efficiently by using Visual BASIC in the personal computer with inexpensive prior. The datas of text, voice, and dynamic images were integrated in this, system by multimedia tools. Also, the database was established to get the expert datas-traffic volume in peak hour, traffic accidents, and road information. as well as general urban informations.

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Development of Traffic Accident Frequency Prediction Model in Urban Signalized Intersections with Fuzzy Reasoning and Neural Network Theories (퍼지 및 신경망이론을 이용한 도시부 신호교차로 교통사고예측모형 개발)

  • Kang, Young-Kyun;Kim, Jang-Wook;Lee, Soo-Il;Lee, Soo-Beom
    • International Journal of Highway Engineering
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    • v.13 no.1
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    • pp.69-77
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    • 2011
  • This study is to suggest a methodology to overcome the uncertainty and lack of reliability of data. The fuzzy reasoning model and the neural network model were developed in order to overcome the potential lack of reliability which may occur during the process of data collection. According to the result of comparison with the Poisson regression model, the suggested models showed better performance in the accuracy of the accident frequency prediction. It means that the more accurate accident frequency prediction model can be developed by the process of the uncertainty of raw data and the adjustment of errors in data by learning. Among the suggested models, the performance of the neural network model was better than that of the fuzzy reasoning model. The suggested models can evaluate the safety of signalized intersections in operation and/or planning, and ultimately contribute the reduction of accidents.

Construction Cost Estimate Modeling of Roundabout at Preliminary Design Stage in Jeju (제주도 내 회전교차로의 초기공사비 예측모델 개발)

  • An, Jin-Hong;Lee, Dong Wook
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.4
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    • pp.1299-1306
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    • 2014
  • Recently, there are many roundabouts installation works which are ordered to provide convenient transportation to road users as well as to eliminate traffic accidents and traffic delays. This study propose an approximate construction cost estimation model for early stages of roundabout construction. The model is designed considering the conditions of the early stage roundabout construction sites in Jeju. The regression equation of approximate construction cost was derived through regression analysis of 25 design data of roundabout construction in Jeju, and it was analyzed to have a high prediction accuracy. Finally, results verifies high prediction accuracy of the derived regression equation. Difference between the estimation cost and the design cost was only 2.3%, 3.7%, and 5.8% that verifies the high accuracy of the proposed approximate construction cost estimation model.

Development of Traffic Accident Rate Forecasting Models for Trumpet IC Exit Ramp of Freeway using Variables Transformation Method (변수변환 기법을 이용한 고속도로 트럼펫IC 유출연결로 교통사고율 예측모형 개발)

  • Yoon, Byoung-Jo
    • International Journal of Highway Engineering
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    • v.10 no.4
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    • pp.139-150
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    • 2008
  • In this study, It is focused on development of the forecasting model about trumpet InterChange(IC) ramp accident because of the frequency of accident in ramp more than highway basic section and trend the increasing accident in ramp. The independent variables was selected through statistical analysis(correlation analysis, multi-collinearity etc) by ramp types(direct, semi-direct and loop). The independent variables and accident rate is non-linear relationship. So it made new variables by transformation of the independent variables. The forecasting models according to exit-ramp type (direct, semi-direct and loop) are built with statistical multi-variable regression using all possible regression method. And the forecasts of the models showed high accuracy statistically. It is expected that the developed models could be employed to design trumpet IC ramp more cost-efficiently and safely and to analyze the causes of traffic accidents happened on the IC ramp.

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