• Journal of Korea Society of Industrial Information Systems
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• v.19 no.5
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• pp.69-79
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• 2014

This paper proposes the Collision Prevention System based on Fuzzy which reasons a risk with the location information of vehicles and pedestrians and prevents collision between vehicles, and between a vehicle and a pedestrian with the reasoned risk. The proposed system provides three functions. First, it identifies a pedestrian's location with his smart phone and a vehicle's location with the GPS equipped in the vehicle. and transfers the identified information to their neighbors. Second, it makes a vehicle and a pedestrian reason a risk by considering a moving direction, a moving speed and road information. Third, it provides a vehicle and a pedestrian with the reasoned information such as route detour, speed reduction, etc. Therefore, the proposed collision prevention system based on Fuzzy not only prevents collision accidents beforehand by reasoning a risk, but also reduces a variety of losses by protecting traffic accident and congestion.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.105-113
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• 2002

As the number of pedestrian accident increases, the reconstruction of an accident becomes important to find the source of the fault. Generally, accidents are reconstructed by the intuition of experts or primitive physics. A reconstruction method is proposed using sophisticated optimization technology. At first, a dynamic simulation model is established for the accident environment. Occupant analysis for automobile crashworthiness is employed. The situation before an accident is identified by optimization. The impact velocity and the position of the pedestrian are utilized as design variables. The design variables are found by minimizing the difference between the simulation and the real accident. The optimization process is performed by linking an occupant analysis program MADYMO to an optimization program VisualDOC. Since the involved analysis is dynamics and highly nonlinear, response surface method is selected for the optimization process. Problems are solved for various situations.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.69-77
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• 2007

This study presents comparison results for pedestrian accident reconstruction models representing the relationship between collision speed and horizontal distance that a body travels while falling and sliding. A set of 49 reliable pedestrian accident cases are applied to compare the existing reconstruction models. In addition, the authors investigate the effects of a set of parameters associated with the effects of the frontal shape of a vehicle on the horizontal distance a pedestrian travels while falling and sliding. It has been revealed that the length of the bumper is the most dominant factor to affect the horizontal distance of pedestrian travel after collision. Further analyses utilizing more accident data need to conducted to develop a more accurate and reliable reconstruction model.

• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.53-66
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• 2013

The major purpose of this study is to evaluate methodologies to predict the injury severity of pedestrian-vehicle collisions. Methodologies to be evaluated and compared in this study include Binary Logistic Regression(BLR), Ordered Probit Model(OPM), Support Vector Machine(SVM) and Decision Tree(DT) method. Valuable insights into applying methodologies to analyze the characteristics of pedestrian injury severity are derived. For the purpose of identifying causal factors affecting the injury severity, statistical approaches such as BLR and OPM are recommended. On the other hand, to achieve better prediction performance, heuristic approaches such as SVM and DT are recommended. It is expected that the outcome of this study would be useful in developing various countermeasures for enhancing pedestrian safety.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.68-83
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• 2019

The number of pedestrian traffic accident fatalities is three times the number of car accidents in South Korea. Serious accidents are caused especially at intersections when the vehicle turns to their right. Various pedestrian collision warning services have been developed, but they are insufficient to prevent dangerous pedestrians. In this study, P2CWS is developed to warn approaching vehicles based on the pedestrians' characteristics. In order to evaluate the performance of the service, actual pedestrian data were collected at the intersection of Daejeon, and comparative analysis was carried out according to pedestrian characteristics. As a result, the performance analysis showed a higher accordance when the characteristics of the pedestrian is considered. Accordingly, we can conclude that identifying pedestrian characteristics in predicting the pedestrian crossing is important.

• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.81-92
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• 2002

An automobile crash with a pedestrian generates a trajectory which is crucial to identify the cause of the crash. Previous researches have been carried out for pedestrian movement using simple explicit formulae. The formulae are derived from elementary physics. Therefore, they could not sufficiently include variables of a vehicle and a pedestrian. To overcome such a limitation, a simulation is utilized for the pedestrian behavior in crash environment. A dynamic software called MADYMO is utilized for the simulation. A simulation model is established. The automobile body and a dummy are modeled with rigid bodies, joints and springs. The simulation results are compared with those from explicit formulae. It is found that the explicit formulae did not fit to pedestrian conditions. Simulations are performed for various velocities of automobiles. Results are discussed for the usage of the simulation.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.139-145
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• 2006

This paper develops pedestrian fatality models capable of producing the probability of pedestrian fatality in collision between vehicles and pedestrians. Probabilistic neural network (PNN) and binary logistic regression (BLR) ave employed in modeling pedestrian fatality pedestrian age, vehicle type, and collision speed obtained from reconstructing collected accidents are used as independent variables in fatality models. One of the nice features of this study is that an iterative sampling technique is used to construct various training and test datasets for the purpose of better performance comparison Statistical comparison considering the variation of model Performances is conducted. The results show that the PNN-based fatality model outperforms the BLR-based model. The models developed in this study that allow us to predict the pedestrian fatality would be useful tools for supporting the derivation of various safety Policies and technologies to enhance Pedestrian safety.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.49-57
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• 2005

This study developed a methodology for estimating the fatality reduction by introducing technical regulation on pedestrian protection in pedestrian-vehicle collisions. Modeling a probabilistic pedestrian fatality model with logistic regression approach was one of keen interests, which employed in estimating the fatality reduction. Collision speed obtained from the accident reconstruction was used in the model development. The effects of fatality reduction, in case various Head Injury Criterion (HIC) and collision speeds are applied for the regulation. were presented as the major outcome of this study. It is expected that the outcome of this study would be an invaluable tool to assist in developing various technologies and policies for pedestrian protection.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.106-118
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• 2014

The objective of this study is to develop a methodology for evaluating the effectiveness of in-vehicle pedestrian warning systems. Driving Simulator-based experiments were conducted to collect data to represent driver's responsive behavior. The braking frequency, lane change duration, and collision speed were used as measure of effectiveness (MOE) to evaluate the effectiveness. Collision speed data obtained from the simulation experiments were further used to predict pedestrian injury severity. Results demonstrated the effectiveness of warning information systems by reducing the pedestrian injury severity. It is expected that the proposed evaluation methodology and outcomes will be useful in developing various vehicular technologies and relevant policies to enhance pedestrian safety.