Reconstruction analysis of traffic accident is done by analyzing diverse data such as the road, accident traces and damage on the automobile. Most data can be a variable in the process of analysis, and measurement error of the data occurs from the investigator, tool and the given environment. Therefore, accident analysis always has some risks of measurement uncertainty. This research quantify the uncertainty in traffic accident analysis by conducting repetitive measurement experiments for variables with high probability of uncertainly such as length (i.e. geometric structure of the road, tire marks) and coefficient of friction. This paper also suggests an analysis result for the uncertainly of photographic observation of automobile crush measurement. These statistical distributions can help determine appropriate ranges for the input data in order to estimate the accident reconstruction uncertainty.
Automobile was first introduced in 1903 in South Korea, the masses of the car was carried out rapidly compared to other countries. However, many people were killed in a traffic accidents and economic loss was occurred due to the spread of the automobile. In South Korea, 2012, traffic accident occurred 223,656 times, 5,392 fatality, 344,565 injured people. In the last five years, about 224,000 accidents per year were occurring. In other words, 610 traffic accidents occur and about 15 people pass away in one day. In addition, the proportion of traffic accidents is first place in the OECD countries and it is very high in the world. Understand occurrence tendency of traffic accident, accident frequency rate of the driver who drives more than 10 years was higher than the novice driver. In addition, as a result of examining the cause of the traffic accident, breach of safe driving obligation appears highest case (125,391 times), and followed by signal violation, break safety distance. Therefore, the majority of traffic accidents occurred by the lack of safety awareness of the driver. In this study, prevent the loss of human life and property in traffic disaster, by establish disaster prevention measures that investigated by questionnaire survey and statistical data of the state of consciousness and driving posture in response to the driving history of the driver.
PURPOSES : The goal of this study is the development of roundabout accident models for urban and non-urban areas. METHODS : This study performed a comparative analysis of the regional factors affecting accidents. Traffic accident data were collected for the period 2010~2014 from the TAAS data set of the Road Traffic Authority. To develop the roundabout accident models, the Poisson and negative binomial regression models were used. A total of 25 explanatory variables such as geometry, and traffic volume were used. RESULTS : The key findings are as follows: First, it was found that the null hypotheses that the number of accidents is the same should be rejected. Second, three Poisson regression accident models, which are statistically significant (${\rho}^2$ of 0.154 and 0.385) were developed. Third, it was noted that although the common variable of the three models (models I~III) is the number of entry lanes, the specific variables are entry lane width, roundabout sign, number of circulatory roadways, splitter island, number of exit lanes, exit lane width, number of approach roads, and truck apron. CONCLUSIONS : The results of this study can provide suggestive countermeasures for decreasing the number of roundabout accidents.
KSCE Journal of Civil and Environmental Engineering Research
/
v.33
no.6
/
pp.2483-2491
/
2013
In order to identify and understand the crucial factors to induce traffic accident, causal relationships between diverse factors and traffic accident occurrence have been investigated continuously. It is one of most important issues all over the world to reduce the number of traffic accidents and deaths by them. Korea government is also stepping up their effort to reduce the number of traffic accidents and mitigate the severity of the accidents by establishing various traffic safety strategies. By introducing the five-day work week and increasing concern of leisure activities, the differences of trip characteristics between weekday and weekend is getting greater. According to this, the patterns and crucial factors of traffic accident occurrence in weekend appear differently from those in weekday. This study aims to understand major different factors affecting accident severity between weekday and weekend using 12,042 incident data occurred on freeways of Korea from 2006 to 2011. The model developed in this study estimated relationships among various exogenous factors of traffic accident by each type using SEM(Structural Equation Model). The result provides that road factors are related to the accident severity for weekday model, while environment factors affects on accident severity for weekend.
Children's accident is a largely preventable public health problem. Little is known. however, about population-based incident and outcome of pediatric accident. From 1997.9 through 1998,8. admission data from emergency center in I city were collected. 1418 patient from 0 through 13 years of age were selected. All children with unintensional accidental problems were identified through coded sheet which categorizes epidemiologic characteristics. The specific purposes of this study are analysis about the characteristics of pediatric accidents. And it aims to produce the basic data necessary for accident prevention policy development. The results of this study were as follows; 1. The number of male children$(62.6\%)$ were higher than female children$(37.4\%)$ 2. The age group from 1 to 3 years represents the highest proportion$(45.4\%)$ of every accidents except on traffic accident. 3. The highest proportion of accident were as follows occured during the June-August$(34\%)$, Sunday$(22.6\%)$, and 17-21 p.m. $(37.2\%)$ 4. The main causes of accident include general trauma$(70.9\%)$, environmental accident$(l6.8\%)$. and traffic accident$(l2.1\%)$, 5. Preschool age group represents more than half$(65.4\%)$ of traffic accident. 6. environmental injury includes burns $(46.6\%)$, foreign body$(43.6\%)$, exposure to poisonous materials$(6.3\%)$. and bite(3.3) This results could be used to develope prevention programs and assist in accident prevention system development. And also these data substantiate that accident prevention program decrease safety-related injury rate in preschool age group must be concentrated on enhancing access to a system to have a significant effect. Furthermore, it is necessary for accident prevention. So several suggestions are described here: 1. Development of parent's educational program for accident prevention and safety education should be done actively. 2. Home safety surveillance system should be initiated. 3. The initiation of children's accident report system could be contribute the analysis and the reduction of accident.
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
/
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.
Eum Han;Giok Park;Heejin Kang;Yoseph Lee;Ilsoo Yun
The Journal of The Korea Institute of Intelligent Transport Systems
/
v.21
no.6
/
pp.36-56
/
2022
Traffic accidents occur in Korea are calculated with the 「Automobile Accident Negligence Ratio Certification Standard」 prepared by the 'General Insurance Association of Korea' and the insurance company's agreement or judgment is made. However, disputes are frequently occurring in calculating the negligence ratio. Therefore, it is thought that a more effective response would be possible if accident type according to the standard could be quickly identified using traffic accident information prepared by police. Therefore, this study aims to develop a model that learns the accident information prepared by the police and classifies it to match the accident type in the standard. In particular, through data mining, keywords necessary to classify the accident types of the standard were extracted from the accident data of the police. Then, models were developed to derive the types of accidents by learning the extracted keywords through decision trees and random forest models.
Choi, Ji Hye;Kang, Soon Yang;Hong, Ji Yeon;Lim, Joon Beom
Journal of the Korean Society of Safety
/
v.31
no.3
/
pp.143-155
/
2016
Recently, a massive loss of life and property is occurring in Korea due to traffic accidents, with the rapid increase in cars. For improvement of traffic safety, the Korea Transportation Safety Authority intensively analyzes accident data in local governments with low traffic safety index, performs a field investigation to extract problems and offers local governments improvements for problems, by conducting the 'Special Survey of Actual Conditions of Traffic Safety' each year, starting 2008. But local governments cannot strongly push forward the improvement projects due to the limited budget and the uncertainty of the improvement plan effects. Therefore, this study suggested a model which applied the Utility concept to the AHP theory, in order to efficiently decide a priority of the improvement plans in accident black spots in consideration of the limited budget of local governments. The number of accidents in each spot for improvement and accident severity, traffic volume, pedestrian volume, the improvement project cost and the accident reduction effect were chosen as evaluation factors for deciding a priority, and data about the improvement plan costs and the accident reduction effects, traffic accidents and traffic volume in the spots to undergo the special research on the real condition of traffic accident in the past were collected from the existing studies. Then, regression analysis was carried out and the Utility Curve of each evaluation factor was computed. Based on the AHP analysis findings, this study devised a priority decision method which calculated the weight and the utility function of each evaluation factor and compared the total utility values. The AHP analysis findings showed that among the evaluation factors, accident severity had the biggest importance and it was followed by the improvement plan cost, the number of accidents, the improvement effect, traffic volume and pedestrian volume. The calculated utility function shows a rise in utility, as the variables of the 5 evaluation factors; the number of accidents, accident severity, the improvement plan effect, traffic volume and pedestrian volume increase and a fall in utility, as the variables of the improvement plan cost increase, since the improvement plan cost is included in the budget spent by a local government.
According to the Korean Traffic Accident Analysis System (TAAS), more than 200,000 traffic accidents occur every year. Also, the statistics including auto insurance companies data show 1.3 million traffic accidents. In the case of TAAS, the types of traffic accidents are simply divided into four; frontal collision, side collision, rear collision, and rollover. However, more detailed information is needed to assess for advanced driver assist systems at intersections. For example, directional information is needed, such as whether the vehicle in the car accident way in a straight or a left turn, etc. This study intends to redefine the type of accident with the more clear driving direction and path by referring to the Negligence standards used in automobile insurance accidents. The standards largely divide five categories of car-to-car/motorcycle /pedestrian/cyclist, and highway, and the each category is classified into dozens of types by status of the traffic signal, conflict situations. In order to present more various accident types for auto insurance accidents, the standards are reclassified driving direction and path of vehicles from crash situations. In results, the car-to-car accidents are classified into 33 accident types, car-to-pedestrian accidents have 19 accident types, car-to-motorcycle accidents have 38 accident types, and car-to-cyclist accidents are derived into 26 types.
The current traffic accident reduction procedure in economic feasibility study does not consider the characteristics of road and V/C ratio. For solving this problem, this paper suggests methods to be able to evaluate safety of each road in construction and improvement through developing accident Prediction model in reflecting V/C ratio Per road types and traffic characters. In this paper as primary process, model is made by tke object of urban roads. Most of all, factor effecting on accident relying on road types is selected. At this point, selecting criteria chooses data obtained from road planning procedure, traffic volume, existence or non-existence of median barrier, and the number of crossing point, of connecting road. and of traffic signals. As a result of analyzing between each factor and accident. all appear to have relatives at a significant level of statistics. In this research, models are classified as 4-categorized classes according to roads and V/C ratio and each of models draws accident predicting model through Poisson regression along with verifying real situation data. The results of verifying models come out relatively satisfactory estimation against real traffic data. In this paper, traffic accident prediction is possible caused by road's physical characters by developing accident predicting model per road types resulted in V/C ratio and this result is inferred to be used on predicting accident cost when road construction and improvement are performed. Because data using this paper are limited in only province of Jeollabuk-Do, this paper has a limitation of revealing standards of all regions (nation).
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