• Journal of Preventive Medicine and Public Health
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• v.37 no.3
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• pp.274-281
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• 2004

Objectives : This study was performed to investigate the injury rates and risk factors for preschool children in Daegu city and Kyungpook province. Method : A questionnaire survey about medically attended injuries during the preschool period was performed in nine primary schools located in Daegu city, Pohang city and Goryung County. The overall injury rate was estimated using person-year. The causes and patterns of the injuries, and their risk factors were examined. Result : A total of 469 medically attended injuries were reported in 330 of the 959 study subjects during the preschool period. The overall annual injury rate was 7.5 per 100 children. The injury rate increased sharply during the period from infant (2.4) to 1 year of age (7.5), and the peak injury rate (9.2) was reported for 5 year olds. The most common causes of injuries were falling (36.0%), followed by being struck by an object (23.7%), and traffic accidents (14.1%). Among the traffic accidents, 72.8% occurred while playing on the road, riding a bicycle or roller-skating. A proportional hazard model showed that males (hazard ratio=1.49, p<0.001 compared with female) and the mother's higher education level (hazard ratio of college or higher= 1.51, p=0.013; high school=1.32, p=0.085 compared with those of middle school or lower) were significant risk factors of childhood injury. Conclusion : The results of this study suggested that efforts for children's safety should be made, especially from the toddler stage, and in male children. To develop a more specific childhood injury prevention program, a surveillance system for injuries should be established. Further study of the relationship between mother's occupation and injury rates is also needed.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.139-147
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• 2007

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.905-910
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• 2022

Drowsy driving requires a lot of social attention because it increases the incidence of traffic accidents and leads to fatal accidents. The number of accidents caused by drowsy driving is increasing every year. Therefore, in order to solve this problem all over the world, research for measuring various biosignals is being conducted. Among them, this paper focuses on non-contact biosignal analysis. Various noises such as engine, tire, and body vibrations are generated in a running vehicle. To measure the driver's heart rate and respiration rate in a driving vehicle with a piezoelectric sensor, a sensor plate that can cushion vehicle vibrations was designed and noise generated from the vehicle was reduced. In addition, we developed a system for classifying whether the driver is sleeping or not by extracting the model using the CNN-LSTM ensemble learning technique based on the signal of the piezoelectric sensor. In order to learn the sleep state, the subject's biosignals were acquired every 30 seconds, and 797 pieces of data were comparatively analyzed.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.89-98
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• 1998

교통사고의 원인은 인적 요인, 차량적 요인, 도로 환경적 요인으로 분류된다. 주어진 도로 환경과 차량 조건하에서는 운전자가 마지막으로 안전을 제어할 책임을 지고 있다. 따라서, 교통사고를 사전에 예방하기 위하여 운전자의 교통법규 위반 행위에 대하여는 도로교통법에 근거하여 징역, 벌금, 구류, 과료, 과태료, 범칙금에 처하고 있다. 교통법규 위반 행위 단속 시에는 교통사고 유발 가능성과 위험도에 따라 단속의 강약을 포함하여 차등화된 처벌이 이루어져야 한다. 교통 범칙금 기준 제시를 위하여 1991~1995년의 5년간 교통사고 및 교통법규 위반을 분석한 결과 전체 교통법규 위반 단속 중 교통사고를 야기하는 동적 위반 행위인 사고관련 위반 행위 단속의 비율이 44%로 일본의 61%에 비해 매우 낮은 수준이다. 따라서 사고유발 가능성에 근거한 교통법규 위반 행위 단속의 강화가 필요하다. 한편 범칙금 부과방안으로 피해도 모형과 빈도 모형을 비교한 결과 교통법규 위반 행위로 인해 발생된 교통사고 비용을 고려한 피해도 모형은 범칙금의 차등화가 분명하지 않고 변별력이 뚜렷이 나타나지 않아 적합하지 않은 것으로 분석되었다. 교통법규 위반 행위에 따른 빈도 모형은 교통사고 건수와 사망사고 건수의 가중치(w)설정을 위해 동적 위반행위가 우리나라와 유사한 일본 자료와 비교한 결과 가중치가 한국=0.7, 일본=0.8일 때 상대적으로 $x^2$가 31.71로 가장 낮게 나타났다. 따라서, 사고건수에 대한 가중치는 0.7로 사망사고에 대한 가중치는 0.3을 적용하였다. 마지막으로 현행 범칙금과 제안된 범칙금을 비교분석하였다.

• 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.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.39-46
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• 2022

As the link between traffic accidents and social and economic losses has been confirmed, there is a growing interest in developing safety policies based on crash data and a need for countermeasures to reduce severe crash outcomes such as severe injuries and fatalities. In this study, we select Daejeon city where the relative proportion of fatal crashes is high, as a case study region and focus on the severity of pedestrian crashes. After a series of data manipulation process, we run machine learning algorithms for the optimal model selection and variable identification. Of nine algorithms applied, AdaBoost and Random Forest (ensemble based ones) outperform others in terms of performance metrics. Based on the results, we identify major influential factors (i.e., the age of pedestrian as 70s or 20s, pedestrian crossing) on pedestrian crashes in Daejeon, and suggest them as measures for reducing severe outcomes.

• Journal of Chest Surgery
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• v.40 no.1 s.270
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• pp.66-68
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• 2007

Traumatic cardiac injury is an extremely serious medical condition. It is possible to overlook a cardiac injury where there is no chest wall trauma. We here report the 47-year-old woman who got a crach car accident and had a tear of the right atrium. The distortion force from a decelerating injury may cause cardiac rupture at a fixed point. The most common symptom that alerts the clinician to a potentially fatal cardiac injury is the change in vital signs. Therefore cardiac injury should be considered in any patient with unexplained hypotension who has experienced decelerating trauma, even without external injury to the chest wall.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.58-70
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• 2019

In the case of a pedestrian traffic accident, it has a large-scale danger directly connected by a fatal accident at the time of the accident. The domestic ITS is not used for intelligent risk classification because it is used only for collecting traffic information despite of the construction of good quality traffic infrastructure. The CNN based pedestrian detection classification model, which is a major component of the proposed system, is implemented on an embedded system assuming that it is installed and operated in a restricted environment. A new model was created by improving YOLO's artificial neural network, and the real-time detection speed result of average accuracy 86.29% and 21.1 fps was shown with 20,000 iterative learning. And we constructed a protocol interworking scenario and implementation of a system that can connect with the ITS. If a pedestrian accident prevention system connected with ITS will be implemented through this study, it will help to reduce the cost of constructing a new infrastructure and reduce the incidence of traffic accidents for pedestrians, and we can also reduce the cost for system monitoring.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.103-113
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• 2005

A pedestrian accident is generally less fully understood than the 'typical' car-to-car collision. For this reason, the analysis of the pedestrian accident is, in many respects, more complicated and demanding. The purpose of this study is to identify clearly the impact point that is the main subject of struggle in pedestrian accidents. In order to develop the model, it is very significant to classify actual accident data including impact velocity. vehicle damage and injury scale of pedestrian. These data were collected from three local branches of RTSA(Road Traffic Safely Authority). The number of collected data were 34 cases and 61.7% of them were fatal accidents. In consequence of analyzing the data by statistical method, it revealed that there is correlation between impact velocity and throw distance. It, also shows that the impact velocity has strong linear correlation to vehicle damage and injury scale. Consequently, reconstruction analysis models of pedestrian accidents considering in local circumstances(such as the physical characteristics of pedestrians and vehicles) was developed However. it is difficult to apply the result of this study to all sorts of pedestrian accidents, because the actual accident data which were used to develop the model were limited. To overcome this limitation, it is necessary to develop an analysis model applicable to diverse circumstances with a wide range of pedestrian accident data on a national basis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.3
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• pp.603-610
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• 2017

Various type of pavement deterioration such as crack, bumpy, pothole is rapidly increasing according to the accelerated environmental changes like heavy rainfall, frequent snowing, difference temperature, etc. Accident related to pothole that cause fatal traffic accidents has been increased more than five times over the next five years starting from 2008. As direct or indirect damage by pothole which caused injuries and car damages increases every year, quicker and more efficient management measures are necessary. This study presents the algorithm for materials quantity take-off. The algorithm was suggested by correlation in pothole size and area. Suggested algorithm were confirmed the validity through the 15 field survey in capital area. According to the results of survey, usually the residual materials at which 5~7 kg was generated decreased to 1~2 kg. It showed that automatic pothole detection system is expected not only to reduce materials and resources, but also to contribute to quality improvements of pavement through more accurate material take-off from the situation of constructing rely on their own judgement.