• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.39-47
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• 2020

In this study, crash situations of representative bus crash types were elicited by analyzing a total of 1,416 bus repair record which were collected in 2018~2019. K-means clustering was used as a methodology for this study. Bus repair record contain the information of repair term, type of bus operation, responsibility of accident, weather condition, road surface condition, type of accident, other party, type of road and type of location for each data. Also, by checking collision parts of each bus repair record, each record was classified by types of collision regions. From this, 760 record are classified to frontal type, 363 record are classified to middle-frontal type, 374 record are classified to middle-rear type and 331 record are classified to rear type. As mentioned, k-means clustering was performed on each type of collision parts. As a result, this study analyzed the severity of bus crash based on actual bus accident data which are based on bus repair record not the crash data from the TAAS. Also, this study presented crash situation of representative bus crash types. It is expected that this study can be expanded to analyzing hydrogen bus crash and defining indicators of hydrogen bus safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.117-130
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• 2017

Bicycles are leading to serious accidents in the event of a side collision, and it is very important to prevent accidents in advance because it is difficult to actively deal with them in a dangerous situation. As a part of the bicycle safety driving support technology, this study establishes bicycle accidents dangerous zone based on bicycle accident data and road property information of digital map nationwide and provides timely safety information to cyclists. The point selected by using actual accident data was called 'dangerous zone', and the potential accident occurrence point generated by modeling based on this 'dangerous zone' was called 'logical dangerous zone'. As a result of the research on the Designation of Logical Bicycle Accident Dangerous Zone, the regional specificity of the bicycle accident points across the nation was generalized to the form of the logical dangerous zone through the network data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1135-1146
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• 2015

This thesis aims to improve the safety of bicycle traffic for activating the use of bicycle, main means of non-powered and non-carbon transportation in order to cope with worldwide crisis such as climate change and energy depletion and to implement sustainable traffic system. In this regard, I analyzed the problem of bicycle roads currently installed and operated, and developed the bicycle accident forecasting model. Following are the processes for this. First, this study presented the current status of bicycle road in Korea as well as accident data, collect the data on bicycle traffic accidents generated throughout the country for recent 3 years (2009~2011) and analyzed the features of bicycle traffic accidents based on the data. Second, this study selected the variable affecting the number of bicycle accidents through accident feature analysis of bicycle accidents at Jeollanam-do, and developed accident forecast model using the multiple regression analysis of 'SPSS Statistics 21'. At this time, the number of accidents due to extension per road types (crossing, crosswalk, other single road) was used. To verify the accident forecast model deduced, this study used the data on bicycle accident generated in Gwangju, 2011, and compared the prediction value with actual number of accidents. As a result, it was found out that reliability of accident forecast model was secured through reconciling with actual number of cases except certain data. Third, this study carried out field survey on the bicycle road as well as questionnaire on satisfaction of bicycle road and use of bicycle for analysis of bicycle road problems, and presented safety improvement measures for the problems deduced as well as bicycle activation plans. This study is considered to serve as the fundamental data for planning and reorganizing of bicycle road in the future, and expected to improve safety of bicycle users and to promote activation of bicycle use as the means of transportation.

• Journal of the Korean Society of Safety
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• v.29 no.5
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• pp.60-66
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• 2014

Depending on the progress of the industrial advances, the use of the thermal oil system in the utility system has been increased, which became an important part in the operation of the plant. However, fire or explosion have occurred due to lack of risk awareness and safety management, more frequently than we know. In this study, by using a questionnaire, actual conditions of safety management in thermal oil system is surveyed and analyzed, it is composed of general, a safety status of the thermal oil system component and the stage of recognition and management in the thermal oil system. These results of this study can be used as basic data to the safety management and the accident prevention of fire or explosion in the workplace.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1181-1188
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• 2021

When abnormal events occur in a nuclear power plant, operators must conduct appropriate abnormal operating procedures. It is burdensome though for operators to choose the appropriate procedure considering the numerous main plant parameters and hundreds of alarms that should be judged in a short time. Recently, various research has applied deep-learning algorithms to support this problem by classifying each abnormal condition with high accuracy. Most of these models are trained with simulator data because of a lack of plant data for abnormal states, and as such, developed models may not have tolerance for plant data in actual situations. In this study, two approaches are investigated for a deep-learning model trained with simulator data to overcome the performance degradation caused by noise in actual plant data. First, a preprocessing method using several filters was employed to smooth the test data noise, and second, a data augmentation method was applied to increase the acceptability of the untrained data. Results of this study confirm that the combination of these two approaches can enable high model performance even in the presence of noisy data as in real plants.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.1-15
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• 2016

This study aims to develop a model by which city bus drivers who are likely to cause an accident can be figured out based on the information about their actual driving records. For this purpose, from the information about the actual driving records of the drivers who have caused an accident and those who have not caused any, significance variables related to traffic accidents are drawn, and the accuracy between models is compared for the classification models developed, applying a discriminant analysis and logistic regression analysis. In addition, the developed models are applied to the data on other drivers' driving records to verify the accuracy of the models. As a result of developing a model for the classification of drivers who are likely to cause an accident, when deceleration ($X_{deceleration}$) and acceleration to the right ($Y_{right}$) are simultaneously in action, this variable was drawn as the optimal factor variable of the classification of drivers who had caused an accident, and the prediction model by discriminant analysis classified drivers who had caused an accident at a rate up to 62.8%, and the prediction model by logistic regression analysis could classify those who had caused an accident at a rate up to 76.7%. In addition, as a result of the verification of model predictive power of the models showed an accuracy rate of 84.1%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2677-2685
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• 2013

Car running data collected from the vehicle is a native image data and sensing data of it. Hence, it can be used as a set of objective data based on which events that took place outside the car can be analyzed and determined. In this paper, we designed and implemented a emergency situation detection system to sense, store, and analyze signals related to car movements, driver's various operation states, collision pulse, etc when a car collision accident occurs on the actual road by sensing and analyzing the car movements and driver's operation status. The suggested system provides information on the driver's reaction right before the collision, operation state of the vehicle, and physical movement. The collected and analyzed data on vehicle running can be utilized to clarify the cause of a collision accident and to handle it in a just manner. Besides, it can contribute to grasping and correcting wrong driving habits of the driver and to saving.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.187-192
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• 2010

Korean railway has run about 110 years since 1989 and played a great role of industrialization in Korea. It is known that rail transport systems have many advantages of being more safe, energy-efficient, and environment-friendly, as compared to other transportation systems. However, railway incidents are often attributed to the failure of safety management and critical to the efficiency of railroad industry. This study reviewed economic, financial, and general statistical information on Korea Railroad. Based on the statistical data, the effect of accidents on railroad management was analyzed. Correlation analysis revealed that railway accident had a negative effect on the gross profit of Korea Railroad. In order to reduce potential risks and incident rate, some recommendations are proposed. Actual or potential applications of this research include safety guidelines for improving efficiency of railroad industry.

• Proceedings of the KIEE Conference
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• 2006.05a
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• pp.34-36
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• 2006

The number of confine-disease of elevator increases every year and then sudden rise, sudden stop, error of level indication, stand; those can bring to uneasiness of elevator passenger and malfunction accidents related life accident are increasing. For confirmation those malfunction accident, we are measuring and analyzing power quality(Sag, Interruption, Harmonic) of the actual site and evaluated the performance for stop and stating by testing the two imitation test equipment with EN12016(2004) standard level. This paper will be used data of the analysis for mutual relation between Power Quality and malfunction and fault of elevator.

• Journal of the Korean Society of Safety
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• v.16 no.2
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• pp.69-74
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• 2001

In this study, we analyzed the accident scenarios of chemical plants through the analysis of lots of chemical accidents and using experts knowledge, and looked into the method of prevention and response. Moreover, we developed a systemic and actual Emergency Response Plan Software(ERPS) that could prevent, prepare and respond totally for the chemical industry facilities using the data from the accident effect estimation from the local society and the geographic information of a chemical plant. The ERPS consists of the information for the plant and process, the consequence analysis and the ERPTA(Emergency Response Plan Tree Analysis). In conclusion, the program developed in this study could help effectively all the chemical industry facilities to prevent and respond to possible accidents.