• Title/Summary/Keyword: road accidents

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A case study on productivity improvement through the analysis of Traffic Safety System (교통안전제도분석을 통한 생산성향상에 관한 사례연구)

  • Kim, Ha-Gon;Sin, Jae-Cheon;Kim, Bu-Yeol;Choe, Jong-Su;Choe, Chun-Ho;Gang, Gyeong-Sik
    • Proceedings of the Safety Management and Science Conference
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    • 2010.11a
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    • pp.41-61
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    • 2010
  • With increasing the quality of life in proportion to the national income, we have had cars as more convenient and safe means of transportation for a long time. The more we have the benefits from cars, the more seriously we should consider problems such as the destruction of the environment by air pollution, traffic accidents, parking problems, traffic congestion, etc. as social cost caused by the increase of cars. Among them, the traffic accidents are very serious, especially the accidents of the business cars occurs five times more than those of the private cars. Therefore if we analyze the cases of the various kinds of syst.em, test the results and apply them to business cars, we will reduce the traffic accidents of business cars.

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Indian Railways: Recent Trends in Control Accidents and Safety Measures for Passengers

  • Kumar, Katta Ashok
    • East Asian Journal of Business Economics (EAJBE)
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    • v.2 no.4
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    • pp.48-55
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    • 2014
  • Indian railways has been regularly in the news albeit for the wrong reasons. The frequency with which train accidents have been taking place has led to serious doubts in the public mind about the safety of rail travel and also the health of the network. Against this background, an attempt is made in this paper to assess the trends in railway accidents for the period from 2000-01 to 2009-10. The paper also highlighted the various measures taken by IR to prevent accidents to ensure safety to the public.

Selection of Accident Frequency Area through Accident Cost Analysis (비용분석을 통한 교통사고 누적지역 선정방안)

  • Lee, Jung-Beom
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.2
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    • pp.33-43
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    • 2022
  • The number of car crashes increases along with the increasing number of vehicles. Hence, diverse initiatives on traffic accidents have been implemented, targeting zero crash fatalities. According to the 3rd Traffic Safety Master Plan of 2016, the current standard selecting road accident black spots prioritizes locations with the high cumulative death toll. While this standard is suitable for roads that a city government manages to some extent, it is not suitable for roads less than 20 meters that a borough (Gu) handles. The roads under the supervision of a borough do not have enough death toll, and thus improvements on its road accident black spots are highly limited. In addition, discovering the causes of traffic accidents is not easy when the number of car accidents is obtained by considering only fatal accidents, which are relatively low in number. Therefore, including all traffic accidents might identify causes of accidents and result in better advancements. Therefore, this research follows rational decision-making and suggests new National Traffic Safety Master Plan standards. These new standards are obtained by comparing accident costs between the location of fatal crashes and road accident black spots. The analysis result shows that considering all types of accidents yields better results. For example, a Three-way Intersection in front of Zion Day Care Center, one of the selected spots under the current standard, has lower road crash costs than Sinchon Intersection, a selected spot under a new standard. Therefore, the study concludes that the standards to select road accident black spots need to include traffic accident severity and road crash costs.

Crash Risks and Crossing Behavior of older pedestrians in Mid-block Signalized Crosswalks (단일로 횡단보도에서의 고령보행자 횡단특성과 사고에 관한 연구)

  • Seo, Geumyeol;Choi, Jaisung;Jeong, Seungwon;Yeon, Junhyoung;Kim, Jeongmin
    • International Journal of Highway Engineering
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    • v.19 no.4
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    • pp.69-78
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    • 2017
  • PURPOSES : In this study, we analyzed the road crossing behavior of older pedestrians on a mid-block signalized crosswalk, and compared it to that of younger pedestrians. In addition, we analyzed the correlation between accidents involving older pedestrians while crossing roads and their behavioral characteristics. Finally, we confirmed the reasons for an increase in accidents involving older pedestrians. METHODS : First, 30 areas with the highest incidence of accidents involving older pedestrians while crossing roads were selected as target areas for analysis. Next, we measured the start-up delay (the time elapsed from the moment the signal turns green to the moment the pedestrian starts walking) and head movement (the number of head turns during crossing a road) of 900 (450 older and 450 younger) pedestrians. The next step was to conduct a survey and confirm the differences in judgment between older and younger pedestrians about approaching vehicles. Finally, we analyzed the correlation between the survey results and traffic accidents. RESULTS : The average start-up delay and head movement of the older pedestrians was 1.58 seconds and 3.15 times, respectively. A definite correlation was obtained between head movement and the frequency of pedestrian traffic accidents. The results of our survey indicate that 17.3% of the older pedestrians and 7.8% of the younger pedestrians have a high crash risk. CONCLUSIONS : Behavioral characteristics of older pedestrians were closely correlated with accidents involving older pedestrians while crossing roads in mid-block signalized crosswalks. Our study indicates that in order to reduce the number of accidents involving older pedestrians, it is necessary to develop an improvement plan including measures such as installation of safety facilities taking the behavioral characteristics of older pedestrians into consideration and their safety education.

A Study on the Development of a Traffic Accident Ratio Model in Foggy Areas (안개지역의 교통사고심각도 모형개발에 관한 연구)

  • Lee, Soo-Il;Won, Jai-Mu;Ha, Oh-Keun
    • Journal of the Korean Society of Safety
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    • v.23 no.6
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    • pp.171-177
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    • 2008
  • As the risk of traffic accidents caused by mists emerged as a social problem, recently safety facilities to be prepared for mists are being actively installed when designing roads. But in some part, the facilities are being installed imprudently without analyzing the extent of occurrences of mists that would increase the risk of traffic accidents and appropriate countermeasures against the occurrences of mists are not being suggested. For that reason, in this study, first questionnaire surveys were executed on road users in order to draw the factors affecting the traffic accidents caused by mists, a mist traffic accident predicting model was developed and an accident seriousness determining model that can determine accident seriousness was developed. In this way, by extracting major factors affecting mist traffic accidents to grasp risk factors in roads to be caused by mists, safety of roads can be enhanced and traffic accidents in road operations can be decreased. As the affecting factors influencing mist traffic accidents, were extracted sightable distances, durations of mists and whether daytime or nighttime as major factors and the plan to install the facilities for the prevention of mist traffic accidents was suggested to prevent the traffic accidents to be caused by those factors and also the plan to operate roads considering sightable distances was suggested to solve the problem of insufficient sightable distances to be caused by mists was suggested. It is judged that the road safety in the areas where mists occur can be improved through foregoing methods.

Deep Learning-based Pothole Detection System (딥러닝을 이용한 포트홀 검출 시스템)

  • Hwang, Sung-jin;Hong, Seok-woo;Yoon, Jong-seo;Park, Heemin;Kim, Hyun-chul
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.1
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    • pp.88-93
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    • 2021
  • The automotive industry is developing day by day. Among them, it is very important to prevent accidents while driving. However, despite the importance of developing automobile industry technology, accidents due to road defects increase every year, especially in the rainy season. To this end, we proposed a road defect detection system for road management by converging deep learning and raspberry pi, which show various possibilities. In this paper, we developed a system that visually displays through a map after analyzing the images captured by the Raspberry Pi and the route GPS. The deep learning model trained for this system achieved 96% accuracy. Through this system, it is expected to manage road defects efficiently at a low cost.

A Study about The Typical Patterns of Driver's Characteristics by The Q Analysis Method (with Traffic Law Violator and Traffic Accident Causer) (Q 분석 방법을 이용한 운전자 운전성향별 유형화에 관한 연구 (교통법규 위반자 및 교통사고 야기자를 중심으로))

  • Jang, Seok-Yong;Jung, Hun-Young;Lee, Won-Gyu;Ko, Sang-Seon
    • Journal of Korean Society of Transportation
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    • v.26 no.1
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    • pp.165-180
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    • 2008
  • The purpose of this research is to propose an effective traffic safety countermeasure to reduce both violations of road traffic acts and accident rates related to the driver's characteristics by measuring them using Q analysis method, a microscopic statistics analysis method. As a result, violators of the road traffic act could be divided into five driving characteristics and causers of traffic accident could be classified into six driving characteristics. By understanding these characteristics, We could establish a proper traffic safety countermeasure for each driving characteristic. The accomplishments of this research are as follows: The first, We could classify the decisive driving characteristics, which cause road traffic acts and traffic accidents, into internal and external causes. The relationship between each driver's characteristic and the occurrence of the road traffic act and traffic accident could be recognized more clearly. We could find the dangerous driver samples who have Accidents proneness. The second, As a result of analyzing the characteristics of these factors, We could sort out and suggest countermeasure for reducing violation of road traffic acts and traffic accidents as a priority countermeasure and complementary countermeasure. Finally, transportation companies most closely related to automobile accidents can judge new personnels on the basis of their driving characteristics before hiring, and also apply this principle to the traffic safety education vigorously.

Driving Conditions and Occupational Accident Management in Large Truck Collisions

  • Jeong, Byung Yong;Lee, Sangbok;Park, Myoung Hwan
    • Journal of the Ergonomics Society of Korea
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    • v.35 no.3
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    • pp.135-142
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    • 2016
  • Objective: Objective of this study is to provide characteristics of injury frequency and severity by driving condition in large truck-related traffic collisions. Background: Traffic accidents involving large trucks draw a lot of attention in accident prevention and management policies since they bring about severe human and financial damages. Method: In order to identify the major risk factors of accidents by driving condition, 255 recognized traffic accidents by large truck drivers were analyzed in terms of time of the day, road type, and shape of the road. Results: The driving conditions in the results are represented by the following form of combination, "Road Type (Non-expressway or Express) - Shape of Roads (Straight, Curved, Downhill, or Intersection) - Time of Accidents (Day or Night)". In the analysis of injury frequency, Non-expressway-Straight-Day condition was the most frequent one. Meanwhile, Expressway-Curved-Day, Non-expressway-Curved-Night and Non-expressway-Intersection-Night were evaluated as high level in view of injury severity. Also, Expressway-Straight-Night is the driving condition that is the highest in risk among the conditions that have to be managed as grade "High". Non-expressway-Straight-Night, Non-expressway-Downhill-Day, and Non-expressway-Curved-Day are also categorized as grade "High". Conclusion and Application: Safety managers in the fields require basic information on accident prevention that can be easily understood. The research findings will serve as a practical guideline for establishing preventive measures for traffic accidents.

Effects of Traffic Islands on Traffic Accidents Reduction (교통섬 설치로 인한 교통사고 감소 효과)

  • Gang, Dong-Su;Lee, Su-Beom;Kim, Yong-Seok;Hong, Ji-Yeon
    • Journal of Korean Society of Transportation
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    • v.28 no.2
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    • pp.21-32
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    • 2010
  • A traffic island, typical channelization facilities, is widely applied to newly road designs and black spots improvement projects as traffic safety measures. However positive effects of a traffic island for traffic safety have not been reported specifically. Accordingly this study analyzed the accidents reduction effectiveness and economics of installing traffic islands under various roadways and traffic conditions. For this purpose normality test, paired t-test and Wilcoxon signed rank test were applied to this study based on traffic accidents, roadways and traffic environments data for 3 years before and after improvement at 54 intersections. The results showed that most of traffic accidents were reduced significantly after installing traffic islands except when traffic islands were installed in outside of cities and farming regions where use efficiency is low, curve sections with poor visibility, poor alignment sections with acceleration/deceleration lanes, road sections where occurs conflicts frequently due to did not install of acceleration/deceleration lanes, and road sections where cross with single lane road.

Selecting Technique of Accident Sections using K-mean Method (K-평균법을 이용한 고속도로 사고분석구간 분할기법 개발)

  • Lee, Ki-Young;Chang, Myung-Soon
    • International Journal of Highway Engineering
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    • v.7 no.4 s.26
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    • pp.211-219
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    • 2005
  • A selection of the analysis section for traffic accidents is used to analyze definitely the cause of accidents sorting similar accidents by a group and to raise the effect of improvement projects deciding the priority of accidents. In the existing method, an uniformly dividing method based on road mileages has been used, which has no consideration for similarities among accidents. Consequently, in recent, a slider-length method considering accident types rather than road mileages is widely used. In this study, using K-mean method, a non-hierarchical grouping technique used in the Cluster Analysis ai a applicatory method for the slider length method, a method classifies accidents that occurred the most nearby mileages into one group is proposed. To verify the proposed method, a comparison between the f-mean method and the dividing method at regular intervals on the data of a total of 25.6km lengths along Kyung-bu freeway in Pusan direction was made so that the K-mean method was proved to an effective method considering the similarities and adjacencies of accidents.

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