• Title/Summary/Keyword: accident rate model

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Evaluating of Risk Order for Urban Road by User Cost Analysis (사용자비용분석을 통한 간선도로 위험순위 산정에 관한 연구)

  • Park, Jung-Ha;Park, Tae-Hoon;Im, Jong-Moon;Park, Je-Jin;Yoon, Pan;Ha, Tae-Jun
    • Journal of Korean Society of Transportation
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    • v.23 no.7 s.85
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    • pp.77-86
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    • 2005
  • Level of service(LOS) is a quantify measure describing operational conditions within a traffic stream, generally, in terms of such service measures as speed, travel time, freedom to measures, traffic interruptions, comfort and convenience. The LOS is leveled by highway facilities according to measure of effectiveness(MOE) and then used to evaluate performance capacity. The current evaluation of a urban road is performed by only a aspect of traffic operation without any concepts of safety. Therefore, this paper presents a method for evaluation of risk order for urban road with new MOE, user cost analysis, considering both smooth traffic operation(congestion) and traffic safety(accident). The user coat is included traffic accident cast by traffic safety and traffic congestion cost by traffic operation. First of all, a number of traffic accident and accident rate by highway geometric is inferred from urban road traffic accident prediction model (Poul Greibe(2001)) Secondly, a user cost is inferred as traffic accident cast and traffic congestion cost is putting together. Thirdly, a method for evaluation of a urban road is inferred by user cost analysis. Fourthly a accident rate by segment predict with traffic accidents and data related to the accidents in $1996{\sim}1998$ on 11 urban road segments, Gwang-Ju, predicted accident rate. Traffic accident cost predict using predicted accident rate, and, traffic congestion cost predict using predicted average traffic speed(KHCM). Fifthly, a risk order are presented by predicted user cost at each segment in urban roads. Finally, it si compared and evaluated that LOS of 11 urban road segments, Gwang-Ju, by only a aspect of traffic operation without any concepts of safety and risk order by a method for evaluation of urban road in this paper.

Analysis of Traffic Accident Severity for Korean Highway Using Structural Equations Model (구조방정식모형을 이용한 고속도로 교통사고 심각도 분석)

  • Lee, Ju-Yeon;Chung, Jin-Hyuk;Son, Bong-Soo
    • Journal of Korean Society of Transportation
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    • v.26 no.2
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    • pp.17-24
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    • 2008
  • Traffic accident forecasting model has been developed steadily to understand factors affecting traffic accidents and to reduce them. In Korea, the length of highways is over 3,000km, and it is within the top ten in the world. However, the number of accidents-per-one kilometer highway is higher than any other countries. The rapid increase of travel demand and transportation infrastructures since 1980's may influence on the high rates of traffic accident. Accident severity is one of the important indices as well as the rate of accident and factors such as road geometric conditions, driver characteristics and type of vehicles may be related to traffic accident severity. However, since all these factors are interacted complicatedly, the interactions are not easily identified. A structural equations model is adopted to capture the complex relationships among variables. In the model estimation, we use 2,880 accident data on highways in Korea. The SEM with several factors mentioned above as endogenous and exogenous variables shows that they have complex and strong relationships.

Developing the Traffic Accident Severity Models by Vehicle Type (차량유형에 따른 교통사고심각도 분석모형 개발)

  • Kim, Kyung-Hwan;Park, Byung-Ho
    • Journal of the Korean Society of Safety
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    • v.25 no.3
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    • pp.131-136
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    • 2010
  • This study deals with the accident models of arterial link sections by vehicle type. The objectives are to analyze the characteristics of accidents, and to develop the models by type. In pursuing the above, this study uses the data of 414 accidents occurred on 24 major arterial links in 2007. The main results analyzed are as follows. First, the number of accidents is analyzed to account for about 47% in passenger car, 15% in SUV and 10% in trucks. Second, 3 Poisson regression models which are all statistically significant are developed using passenger car, SUV and truck as dependant variables. Finally, AADT and the number of traffic islands as common variables, and the number of pedestrian crossings, lanes, connecting roads, intersections(4-Leg), rate of medians and the number of bus stops as specific variables of the models are selected.

Upper Legform Impact Test of the EURO-NCAP Protocol using a Pedestrian Dummy Model (보행자 더미모델을 이용한 EURO-NCAP 상부다리모형 평가시험 방법에 대한 분석)

  • Park, Sang-ok;Choi, Wook-han;Son, Dae-Geun;Park, Gyung-Jin;Lee, EunDok;Kwon, Hae Boung
    • Journal of Auto-vehicle Safety Association
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    • v.9 no.4
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    • pp.14-19
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    • 2017
  • The mortality rate of car-pedestrian accidents is quite high compared to the frequency of accident. Recently, governments and insurance companies tend to establish and implement new safety standards for pedestrian protection such as EURO-NCAP and K-NCAP. The performance for the pedestrian protection has been gradually improved, but it is still insufficient. Therefore, various studies for the pedestrian protection are being carried out. The car-pedestrian accident is simulated in order to study to the upper legform test of the EURO-NCAP protocol. A pedestrian dummy model is employed and the results are discussed.

An In-Tunnel Traffic Accident Detection Algorithm using CCTV Image Processing (CCTV 영상처리를 이용한 터널 내 사고감지 알고리즘)

  • Baek, JungHee;Min, Joonyoung;Namkoong, Seong;Yoon, SeokHwan
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.2
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    • pp.83-90
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    • 2015
  • Almost of current Automatic Incident Detection(AID) algorithms involve the vulnerability that detects the traffic accident in open road or in tunnel as the traffic jam not as the traffic accident. This paper proposes the improved accident detection algorithm to enhance the detection probability based on accident detection algorithms applied in open roads. The improved accident detection algorithm provides the preliminary judgment of potential accident by detecting the stopped object by Gaussian Mixture Model. Afterwards, it measures the detection area is divided into blocks so that the occupancy rate can be determined for each block. All experimental results of applying the new algorithm on a real incident was detected image without error.

HFACS-K: A Method for Analyzing Human Error-Related Accidents in Manufacturing Systems: Development and Case Study (제조업의 인적오류 관련 사고분석을 위한 HFACS-K의 개발 및 사례연구)

  • Lim, Jae Geun;Choi, Joung Dock;Kang, Tae Won;Kim, Byung Chul;Ham, Dong-Han
    • Journal of the Korean Society of Safety
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    • v.35 no.4
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    • pp.64-73
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    • 2020
  • As Korean government and safety-related organizations make continuous efforts to reduce the number of industrial accidents, accident rate has steadily declined since 2010, thereby recording 0.48% in 2017. However, the number of fatalities due to industrial accidents was 1,987 in 2017, which means that more efforts should be made to reduce the number of industrial accidents. As an essential activity for enhancing the system safety, accident analysis can be effectively used for reducing the number of industrial accidents. Accident analysis aims to understand the process of an accident scenario and to identify the plausible causes of the accident. Accident analysis offers useful information for developing measures for preventing the recurrence of an accident or its similar accidents. However, it seems that the current practice of accident analysis in Korean manufacturing companies takes a simplistic accident model, which is based on a linear and deterministic cause-effect relation. Considering the actual complexities underlying accidents, this would be problematic; it could be more significant in the case of human error-related accidents. Accordingly, it is necessary to use a more elaborated accident model for addressing the complexity and nature of human-error related accidents more systematically. Regarding this, HFACS(Human Factors Analysis and Classification System) can be a viable accident analysis method. It is based on the Swiss cheese model and offers a range of causal factors of a human error-related accident, some of which can be judged as the plausible causes of an accident. HFACS has been widely used in several work domains(e.g. aviation and rail industry) and can be effectively used in Korean industries. However, as HFACS was originally developed in aviation industry, the taxonomy of causal factors may not be easily applied to accidents in Korean industries, particularly manufacturing companies. In addition, the typical characteristics of Korean industries need to be reflected as well. With this issue in mind, we developed HFACS-K as a method for analyzing accidents happening in Korean industries. This paper reports the process of developing HFACS-K, the structure and contents of HFACS-K, and a case study for demonstrating its usefulness.

Analysis of risk factors of the fisherman's in coastal purse seine fishery using the accident compensation insurance proceeds payment data of NFFC (수협 어선원 재해보상보험 자료를 이용한 연안선망어업 위험요인 분석)

  • CHOI, Kyu-Suk;LEE, Chun-Woo;PARK, Su-bong;JANG, Yong-Suk;LEE, Yoo-Won
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.56 no.4
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    • pp.340-346
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    • 2020
  • In this study, the risk factors of coastal purse seine fisherman were analyzed through a survey of fishery workers of coastal purse seine fishery and the accident compensation insurance data of the fisheries workers of the National Federation of Fisheries Cooperatives (NFFC). The classified fishing operation accident data was analyzed through 4M (Man, Machine, Media, Management) model of the National Transportation Safety Board (NTSB) and the accident prevention measures were presented using Harvey's 3E (Engineering, Education, Enforcement) model. The rate of accidents on coastal purse seinens each year was 75.8‰, 36.7‰ and 74.8‰ from 2015 to 2017. The accident frequency resulting from slipping was the highest, and the risk of a contact with gear was low. When comparing each insurance data, the average value of the contact with gear accident was the highest. This research result is expected to be important data in identifying and preventing safety hazards of coastal purse seiner fisherman in the future.

The Analysis of Risk according to Traffic Accident Types by Novice and Experienced Drivers in Korea (초보 및 일반운전자의 교통사고유형별 위험도 비교분석)

  • Kim, Gi-Yong;Jang, Myeong-Sun;O, Cheol
    • Journal of Korean Society of Transportation
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    • v.27 no.3
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    • pp.17-28
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    • 2009
  • To analyze the risk according to accident types by novice and experienced drivers, it is used the accidents data which occurred for 2 years(2005~2006) in Korea. It is defined that novice driver is a people who is not passed 1 year after getting a driving licence and experienced driver is a people who is passed 1 year in this study. It is used a risk model to compare and analyze about the risk between two groups. The risk model is developed to apply together two variables which is accidents frequency and severity. Then it is used a conceptual weight to find that proper rate between accident frequency and fatal accident frequency. It is found a weight($\omega=0.6$) to suitable value to apply a risk model. The results showed that collision with obstacles, angle collision($90^{\circ}$) types to novice driver group have bigger risk than experienced driver group.

Development of Quantitative Risk Assessment Methodology for the Maritime Transportation Accident of Merchant Ship (상선 운항 사고의 양적 위기평가기법 개발)

  • Yim, Jeong-Bin
    • Journal of Navigation and Port Research
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    • v.33 no.1
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    • pp.9-19
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    • 2009
  • This paper describes empirical approach methodology for the quantitative risk assessment of maritime transportation accident (MTA) of a merchant ship. The principal aim of this project is to estimate the risk of MTA that could degrade the ship safety by analyzing the underlying factors contributing to MTA based on the IMO's Formal Safety Assessment techniques and, by assessing the probabilistic risk level of MTA based on the quantitative risk assessment methodology. The probabilistic risk level of MTA to Risk Index (RI) composed with Probability Index (PI) and Severity Index (SI) can be estimated from proposed Maritime Transportation Accident Model (MTAM) based on Bayesian Network with Bayesian theorem Then the applicability of the proposed MTAM can be evaluated using the scenario group with 355 core damaged accident history. As evaluation results, the correction rate of estimated PI, $r_{Acc}$ is shown as 82.8%, the over ranged rate of PI variable sensitivity with $S_p{\gg}1.0$ and $S_p{\ll}1.0$ is shown within 10%, the averaged error of estimated SI, $\bar{d_{SI}}$ is shown as 0.0195 and, the correction rate of estimated RI, $r_{Acc}$(%), is shown as 91.8%. These results clearly shown that the proposed accident model and methodology can be use in the practical maritime transportation field.

Effects of Input Variables in Radiological Accident Consequence Assessment

  • Han, Moon-Hee;Hwang, Won-Tae;Kim, Eun-Han;Suh, Kyung-Suk;Park, Young-Gil
    • Proceedings of the Korean Nuclear Society Conference
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    • 1998.05b
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    • pp.659-664
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    • 1998
  • The importance of input wariables of real-time accident consequence assessment model has been analyzed. Partial correlation coefficients of input variables related to the plume and the ingestion exposure have been estimated using latino hypercube sampling technique. It is known that wind speed and growth dilution rate are the most important variable in plume and ingestion exposure, respectively.

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