• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.119-130
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• 2010

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.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.127-136
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• 2012

Multi-car rear-end collision accidents have three categories: sequential collision from the rear which is commonly referred to as chain reaction collision, sequential collision from the front, and mixed-order collision. This paper suggests several effective methods of reconstruction analysis for multi-car rear-end collision accidents. First, by incorporating the traditional empirical method which uses vehicle damage caused by brake dive and passenger injuries, with results of theoretical analysis made within mechanics of rigid body, it is made possible for the method to be put to immediate practical use. A methodology to precisely analyze multi-car rear-end collision accidents was suggested using a simulation program simultaneously with a video event data recorder which is starting to be widely used in domestic vehicles. To go beyond the simple intuitive analysis of the video event data recorder, the simulation analysis based on the results of video analysis was executed to acquire various information, so that the causes and responsibility could be clearly stated.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.125-134
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• 2011

In order to reconstruct vehicle-pedestrian collision accidents, this paper presents a fuzzy tool to estimate accurately the impact velocity of the vehicle using parameters which could be easily collectable at the accident scene. The fuzzy rules and membership functions were set up using number of over 200 domestic and foreign data from accidents and empirical tests and 700 data from multibody simulation experiments. The developed fuzzy tool deduces the category of pedestrian trajectory and impact speed of the vehicle using 4 membership functions and 2 logic rules. The membership function of throw distance was differently set according to the deduced category of trajectories. The implemented fuzzy program was validated through comparing with the domestic and foreign empirical data. The output results agree very well in impact velocities of vehicle resulting the accuracy and usefulness of the developed tool in the reconstruction analysis of vehicle-pedestrian collision accidents.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.60-65
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• 2021

The event data recorders (EDR) have been used as a device to help understand traffic accidents. With the recent development of autonomous vehicle (AV), it has become important to prepare the new EDR for AV. Therefore, the purpose of this study is to propose the direction of EDR-AV recording. First of all, the recent EDR data elements and the data elements of AV under discussion at UNECE WP29 EDR/DSSAD (Data Storage System for Automated Driving) were analyzed. The consumer complaint database in Motor Vehicle Recall Center in Korea was analyzed in order to utilize cases of domestic traffic accidents related to advanced driver assistance systems (ADAS). Consequently, problems with existing EDR were identified through unclear accident cases related to ADAS. In the future, it was proposed to record images in which the ADAS perception systems recognize the surroundings of the accident site as an EDR-AV recording item.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.615-622
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• 2015

Recently Digital-TachoGraph(DTG) was mounted mandatorily in commercial vehicles(Taxi, Bus, etc.). DTG records accurate and detailed information of the running state of vehicles related to traffic accident, such as Time, Distance, Velocity, RPM, Brake ON/OFF, GPS, Azimuth, Acceleration. Thus those standardized data can play an important role in traffic accident investigation and reconstruction. To develope the accurate and objective method using the DTG data for the reconstruction of traffic accident, we had conducted several tests such as driving test, high speed circuit test, braking test, slalom test at Korea Automobile Testing & Research Institute(KATRI), and collision test at Korea Automobile insurance repair Research and Training center(KART) with the vehicle equipped with several DTG. Development of the program which enables the reading and analysis of the DTG data was followed. In the experiments, we have found velocity error, RPM error, brake signal error and azimuth error in several products, and also non-continuous event data. The cause of these errors was deduced to be related to the correction factor, the durability of electronic parts and the algorithm.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.427-441
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• 2021

Purpose: This study proposes a method for developing a model that predicts the probability of traffic accidents in advance to prevent the most frequent traffic accidents in the military. Method: For this purpose, CRISP-DM (Cross Industry Standard Process for Data Mining) was applied in this study. The CRISP-DM process consists of 6 stages, and each stage is not unidirectional like the Waterfall Model, but improves the level of completeness through feedback between stages. Results: As a result of modeling the same data set as the previously constructed accident investigation data for the entire group, when the classification criterion was 0.5, Significant results were derived from the accuracy, specificity, sensitivity, and AUC of the model for predicting traffic accidents. Conclusion: In the process of designing the prediction model, it was confirmed that it was difficult to obtain a meaningful prediction value due to the lack of data. The methodology for designing a predictive model using the data set was proposed by reorganizing and expanding a data set capable of rational inference to solve the data shortage.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.107-115
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• 2000

We suggest a method which solves the planar, two vehicle collision reconstruction problem. The method based on the Principle of impulse and momentum determines the pre-impact velocity components from Post-impact velocity components, vehicle Physical data and collision geometry. A novel feature is that although the impact coefficients such as the restitution coefficient and the impulse ratio are unknown, the method can estimate automatically the coefficients and calculate the pre-impact velocity components. This reverse calculation is important for vehicle accident reconstruction, since the pre-impact velocities are unknown and Post-impact Phase is the starting Point in a usual collision analysis. However. an inverse solution is not always Possible with the analytical rigid-body impact model. Mathematically, one does not exist under the common velocity condition. On the other hand, our method has a capability of reverse calculation under the condition if the absorbed energy during the collision process can be estimated using the crush profile. To validate the developed collision reconstruction a1gorithm, we use car-to-car collision test results. The analysis and experimental results agree well in the impact coefficients and the Pre-impact velocity components.

• Journal of the Korean Institute of Gas
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• v.25 no.4
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• pp.1-9
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• 2021

The process and facilities of modern chemical plants are becoming increasingly complex, there is possibility of potential risk. Internal chemicals generate stress concentration when operated due to turbulence, laminar flow, pressure, temperature, friction, etc. It causes cumulative fatigue damage, which can damage or rupture chemical facilities and devices. The statistics of chemical accidents found that the highest rate of occurrence was in summer, and in the last five years statistics on chemical accidents, leakage incidents make up a decent percentage of accidents. Chemical leaks can cause serious human damage and economic damage, including explosions and environmental pollution. In this study, based on the leak accident of chemical plant, the risk analysis, and damage effects assessment were estimated using a 3D scanner and FLACS. As a result, if chemicals leak in summer, the risk is higher than in other seasons, the seasonal safety management measures, and countermeasure were estimated.

• Journal of Auto-vehicle Safety Association
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• v.12 no.3
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• pp.52-60
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• 2020

Usage of EDR(Event Data Recorder) report for traffic accident analysis is currently increasing due to government regulation of EDR data release. Nevertheless, a lot of investigators simply adopt by comparing the number of ignition cycles(crash) at event to the number of ignition cycles(download) without an exact judgment whether event data occurred by this accident or not. In the EDR report, besides ignition cycles, there are many factors such as event record type, algorithm active(rear/rollover/side/frontal), time between events, event severity status(rollover/rear/right side/reft side/frontal), belt switch circuit status, driver/passenger pretensioner/air-bag deployment, PDOF(Principal Direction of Force) by ΔV to be able to decide whether or not to adopt. also the event data is considered enough to vehicle damaged state, accident situation at the scene of the accident. and there is described in "all data should be examined in conjunction with other available physical evidence from the vehicle and scene" in the CDR(Crash Data Retrieval) report. Therefore many investigators have to decide whether or not to adopt after they consider sufficiently to above factors when they are the traffic accident analysis and investigate the causes of a accident on the adopted event data. In this paper, we report to traffic accident investigators notable points and analysis methods on the basis of thousands of cases and the results of one's own experiment in NFS(National Forensic Service).

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.106-113
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• 2021

In this study, The behavior of an autonomous vehicle in an intersection accident situation is predicted. Based on a representative intersection accident situation from actual intersection accident database, simulation was performed by applying the automatic emergency braking algorithm used in the autonomous driving system. Accident reconstruction was performed based on the accident report of the representative accident situation. After applying the autonomous driving system to the accident-related vehicle, the tendency of intersection accidents that may occur in autonomous vehicles was identified and analyzed.